Find Your Dream Data Scientist Job in India

At o9 Solutions, our mission is clear: be the Most Valuable Platform (MVP) for enterprises. With our AI-driven platform - the o9 Digital Brain - we integrate global enterprises' siloed planning capabilities, helping them capture millions and, in some cases, billions of dollars in value leakage. But our impact doesn't stop there. Businesses that plan better and faster also reduce waste, which drives better outcomes for the planet, too.

We're on the lookout for the brightest, most committed individuals to join us on our mission. Along the journey, we'll provide you with a nurturing environment where you can be part of something truly extraordinary and make a real difference for companies and the planet

What you'll do for us:

• Apply a variety of machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations etc.) to their real-world advantages/drawbacks
• Develop and/or optimize models for demand sensing/forecasting, optimization (Heuristic, LP, GA etc), Anomaly detection, Simulation and stochastic models, Market Intelligence etc.
• Use latest advancements in AI/ML to solve business problems
• Analyze problems by synthesizing complex information, evaluating alternate methods, and articulating the result with the relevant assumptions/reasons
• Application of common business metrics (Forecast Accuracy, Bias, MAPE) and the ability to generate new ones as needed.
• Develop or optimize modules to call web services for real time integration with externa systems
• Work collaboratively with Clients, Project Management, Solution Architects, Consultants and Data Engineers to ensure successful delivery of o9 projects

What you'll have:

• Experience: 4+ Years of experience in time series forecasting in scale using heuristic-based hierarchical best-fit models using algorithms like exponential smoothing, ARIMA, prophet and custom parameter tuning.
• Experience in applied analytical methods in the field of Supply chain and planning, like demand planning, supply planning, market intelligence, optimal assortments/pricing/inventory etc.
• Should be from a statistical background.
• Education: Bachelors Degree in Computer Science, Mathematics, Statistics, Economics, Engineering or related field
• Languages: Python and/or R for Data Science
• Skills: Deep Knowledge of statistical and machine learning algorithms, building scalable ML frameworks, identifying and collecting relevant input data, feature engineering, tuning, and testing.
• Characteristics: Independent thinkers Strong presentation and communications skills
• We really value team spirit: Transparency and frequent communication is key. At o9, this is not limited by hierarchy, distance, or function.

Nice to have:

• Experience with SQL, databases and ETL tools or similar is optional but preferred
• Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies
• Experience with Deep Learning frameworks such as Keras, Tensorflow or PyTorch is preferable
• Experience in implementing planning applications will be a plus
• Understanding of Supply Chain Concepts will be preferable
• Masters Degree in Computer Science, Applied Mathematics, Statistics, Engineering, Business Analytics, Operations, or related field

What we'll do for you

• Competitive salary with stock options to eligible candidates
• Flat organization: With a very strong entrepreneurial culture (and no corporate politics)
• Great people and unlimited fun at work
• Possibility to make a difference in a scale-up environment.
• Opportunity to travel onsite in specific phases depending on project requirements.
• Support network: Work with a team you can learn from everyday.
• Diversity: We pride ourselves on our international working environment.
• Work-Life Balance:
• Feel part of A team:

How the process works

• Apply by clicking the button below
• You'll be contacted by our recruiter, who'll fill you in on all things at o9, give you some background about the role and get to know you. They'll contact you either via video call or phone call - whatever you prefer.
• During the interview phase, you will meet with technical panels for 60 minutes. The recruiter will contact you after the interview to let you know if we'd like to progress your application.
• We will have 2 rounds of Technical discussion followed by a Hiring Manager discussion.
• Our recruiter will let you know if you're the successful candidate. Good luck!

More about us

o9 Solutions is one of the fastest-growing technology companies in the world today. Our mission is to digitally transform planning and decision-making for the enterprise and the planet. Our culture is high-energy and drives us to aim 10x in everything we do.

Our platform, the o9 Digital Brain, is the premier AI-powered, cloud-native platform driving the digital transformations of major global enterprises including Google, Walmart, ABInBev, Starbucks and many others.

Our headquarters are located in Dallas, with offices in Amsterdam, Paris, London, Barcelona, Madrid, Sao Paolo, Bengaluru, Tokyo, Seoul, Milan, Stockholm, Sydney, Shanghai, Singapore and Munich.

o9 is an equal opportunity employer and seeks applicants of diverse backgrounds and hires without regard to race, colour, gender, religion, national origin, citizenship, age, sexual orientation or any other characteristic protected by law

At o9 Solutions, our mission is clear: be the Most Valuable Platform (MVP) for enterprises. With our AI-driven platform - the o9 Digital Brain - we integrate global enterprises' siloed planning capabilities, helping them capture millions and, in some cases, billions of dollars in value leakage. But our impact doesn't stop there. Businesses that plan better and faster also reduce waste, which drives better outcomes for the planet, too.

We're on the lookout for the brightest, most committed individuals to join us on our mission. Along the journey, we'll provide you with a nurturing environment where you can be part of something truly extraordinary and make a real difference for companies and the planet

What you'll do for us:

• Apply a variety of machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations etc.) to their real-world advantages/drawbacks
• Develop and/or optimize models for demand sensing/forecasting, optimization (Heuristic, LP, GA etc), Anomaly detection, Simulation and stochastic models, Market Intelligence etc.
• Use latest advancements in AI/ML to solve business problems
• Analyze problems by synthesizing complex information, evaluating alternate methods, and articulating the result with the relevant assumptions/reasons
• Application of common business metrics (Forecast Accuracy, Bias, MAPE) and the ability to generate new ones as needed.
• Develop or optimize modules to call web services for real time integration with externa systems
• Work collaboratively with Clients, Project Management, Solution Architects, Consultants and Data Engineers to ensure successful delivery of o9 projects

What you'll have:

• Experience: 4+ Years of experience in time series forecasting in scale using heuristic-based hierarchical best-fit models using algorithms like exponential smoothing, ARIMA, prophet and custom parameter tuning.
• Experience in applied analytical methods in the field of Supply chain and planning, like demand planning, supply planning, market intelligence, optimal assortments/pricing/inventory etc.
• Should be from a statistical background.
• Education: Bachelors Degree in Computer Science, Mathematics, Statistics, Economics, Engineering or related field
• Languages: Python and/or R for Data Science
• Skills: Deep Knowledge of statistical and machine learning algorithms, building scalable ML frameworks, identifying and collecting relevant input data, feature engineering, tuning, and testing.
• Characteristics: Independent thinkers Strong presentation and communications skills
• We really value team spirit: Transparency and frequent communication is key. At o9, this is not limited by hierarchy, distance, or function.

Nice to have:

• Experience with SQL, databases and ETL tools or similar is optional but preferred
• Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies
• Experience with Deep Learning frameworks such as Keras, Tensorflow or PyTorch is preferable
• Experience in implementing planning applications will be a plus
• Understanding of Supply Chain Concepts will be preferable
• Masters Degree in Computer Science, Applied Mathematics, Statistics, Engineering, Business Analytics, Operations, or related field

What we'll do for you

• Competitive salary with stock options to eligible candidates
• Flat organization: With a very strong entrepreneurial culture (and no corporate politics)
• Great people and unlimited fun at work
• Possibility to make a difference in a scale-up environment.
• Opportunity to travel onsite in specific phases depending on project requirements.
• Support network: Work with a team you can learn from everyday.
• Diversity: We pride ourselves on our international working environment.
• Work-Life Balance:
• Feel part of A team:

How the process works

• Apply by clicking the button below
• You'll be contacted by our recruiter, who'll fill you in on all things at o9, give you some background about the role and get to know you. They'll contact you either via video call or phone call - whatever you prefer.
• During the interview phase, you will meet with technical panels for 60 minutes. The recruiter will contact you after the interview to let you know if we'd like to progress your application.
• We will have 2 rounds of Technical discussion followed by a Hiring Manager discussion.
• Our recruiter will let you know if you're the successful candidate. Good luck!

More about us

o9 Solutions is one of the fastest-growing technology companies in the world today. Our mission is to digitally transform planning and decision-making for the enterprise and the planet. Our culture is high-energy and drives us to aim 10x in everything we do.

Our platform, the o9 Digital Brain, is the premier AI-powered, cloud-native platform driving the digital transformations of major global enterprises including Google, Walmart, ABInBev, Starbucks and many others.

Our headquarters are located in Dallas, with offices in Amsterdam, Paris, London, Barcelona, Madrid, Sao Paolo, Bengaluru, Tokyo, Seoul, Milan, Stockholm, Sydney, Shanghai, Singapore and Munich.

o9 is an equal opportunity employer and seeks applicants of diverse backgrounds and hires without regard to race, colour, gender, religion, national origin, citizenship, age, sexual orientation or any other characteristic protected by law

T

TrueID is at the forefront of digital transformation in the realm of biometric-based identity management, emphasizing the pivotal role of digital identities in modern-day businesses such as fintech, banking, and e-commerce. Our team members are given exceptional opportunities to work on cutting-edge projects, pushing the boundaries of digital transformation in identity management in the banking, fintech domains and ecommerce domains.

At TrueID, we offer an inspiring work environment that fosters innovation and creativity, allowing team members to contribute to groundbreaking digital identity projects. All TrueID employees are engaged on overseas projects giving them exposure to diverse cultures and perspectives enhancing their professional growth in an increasingly digitalized world. TrueID's commitment to driving digital innovation has made the company a thought leader in shaping the future landscape of digital transformation to manage digital identities.

Job Description:

TrueID () is looking to hire a talented Data Scientist with 5 to 8 years of experience to join our team and develop high-impact, scalable predictive analytics solutions. You will leverage advanced Gen AI, AI/ML to build solutions build data pipelines, and be part of the productization team responsible for delivering robust solutions for our clients.

Responsibilities

• Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.
• Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.
• Analyze structured and unstructured data to identify trends, patterns, and actionable business insights.
• Perform data preprocessing, feature engineering, model development, deployment and model evaluation
• Evaluate, fine-tune, and optimize AI/ML models to improve accuracy, performance, scalability, and reliability.
• Develop APIs and services for model deployment and integration with enterprise systems.
• Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.
• Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate.

Experience & Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• 5 to 8 years of hands-on experience in Data Science, Machine Learning, Predictive Analytics
• Strong proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.
• Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data-driven decision making.
• Apply statistical and machine learning techniques to analyze large datasets, identify patterns, build predictive models, and generate actionable business insights.
• Experience with Generative AI technologies, Large Language Models (LLMs)
• Experience working with SQL and NoSQL databases, data warehouses, and big data technologies.
• Familiarity with cloud platforms such as AWS, and containerization technologies such as Docker and Kubernetes.
• Experience in building REST APIs and integrating AI models into production environments.
• Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimization methods.
• Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.

Preferred Qualifications

• Experience using graph technologies such as Neo4j and graph data modeling for fraud detection, relationship analysis, or customer intelligence.
• Familiarity with data governance, and data quality frameworks.
• Exposure to statistical methods and techniques for entity matching and identity resolution.

We are looking for immediate joiners

Interested candidates can send your resume to

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

Role Overview

As a Data Scientist in our Advertising Technology division, you will design and implement machine learning models and optimization algorithms to improve ad delivery efficiency and maximize campaign performance. You will own the end-to-end lifecycle, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.

Key Responsibilities

• Define optimization problems for ad delivery, including KPIs, metrics, and monitoring dashboard
• Perform data preprocessing, feature engineering, and model development for:
• Price optimization
• CTR/CVR prediction
• Creative performance analysis
• Conduct offline evaluations and simulations, followed by online deployment and A/B testing
• Implement MLOps practices such as:
• Training and inference pipeline
• Drift detection
• Automated rollback mechanism
• Governance for quality and privac
• Collaborate with product, engineering, and operations teams to translate business requirements into actionable data solution

Technical Environment

• Cloud platforms: GCP (or equivalent such as AWS/Azure)
• Big data tools: BigQuery, Dataflow, Pub/Sub
• Distributed systems and real-time processing architectures
• Programming languages: Python, Go
• Infrastructure automation: Terraform, Ansible

Mandatory Qualifications

• 3+ years of experience in data analysis and machine learning using Python and SQL
• Proficiency in libraries and tools such as Pandas, NumPy, scikit-learn, and data visualization
• Hands-on experience with large-scale data processing (e.g., Spark, BigQuery) and reproducible analytics workflows
• Strong foundation in:
• Statistics and probability
• Experimental design (A/B testing, causal inference)
• Experience building and deploying ML models (regression, classification, tree-based methods, basic neural networks) with robust evaluation strategies
• Knowledge of digital advertising concepts (CTR/CVR prediction, bidding strategies, KPI optimization) or similar optimization domains
• Practical experience with production ML systems, including monitoring and drift detection
• Strong communication skills for stakeholder collaboration and presenting analytical insights
• Bachelor's or higher degree in Computer Science, Statistics, Applied Mathematics, or a related field
• Business-level English proficiency (e.g., TOEIC 800+)

Preferred Qualifications

• Understanding of ad auction mechanisms (first-price/second-price auctions, bid shading, reserve price optimization)
• Experience with advanced optimization techniques:
• Bayesian optimization
• Multi-armed bandits
• Reinforcement learning
• Familiarity with creative optimization and generative AI for ad content
• Experience with real-time streaming platforms (Kafka, Flink, Beam) and online inference systems
• Knowledge of MLOps best practices:
• Feature stores
• CI/CD pipelines
• Containerization
• Monitoring
• Hands-on experience with cloud platforms such as GCP, AWS, or Azure

About the Company:

"Re-imaging credit and payments from First Principles".

Credit cards haven't changed much for over half a century, so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - India's best metal credit card reimagined for the mobile generation, built with full-stack tech and backed by principles of simplicity and transparency.

Opportunity:

We are looking for a Senior Data Scientist to build and own data science solutions that provide competitive differentiation for our customers and business. In this role, you will be critical in shaping the credit card portfolio strategy across the entire customer lifecycle.

Role Overview:

• Role: Senior Data Scientist
• Experience Range: 5 – 7 years
• Work Location: Aundh/Baner - Pune (Work from Office ONLY)

What will you do:

As a key member of our growing team, you will be responsible for owning portfolio metrics and delivering on agreed KPIs. Your role will involve:

• Portfolio Ownership: End-to-end ownership of customer management, covering activation, credit line management, risk-based pricing, and ENR uplift.
• Strategic Analysis: Performing deep-dive data analysis to identify high-impact opportunities and uncover trends ac

Key Responsibilities:

● Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML

(Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI).

● Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculum

to reflect current industry tools, techniques, and best practices, incorporating your

professional experience and case studies.

● Mentor Student Projects: Guide students through hands-on AI/ML projects, providing

technical direction, code reviews, and feedback based on industry standards.

● Guide & Mentor Students: Advise students on developing practical skills,

understanding career paths in AI/ML, and preparing for internships and job placements.

● Stay Current: Bring the latest AI/ML research, tools, and industry trends into the

classroom.

● Collaborate: Work closely with other expert faculty and staff to create a unified and

effective learning experience.

● Assess Practical Skills: Design and evaluate assignments, projects, and assessments

focused on real-world applications.

Qualifications and Requirements:

● Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science,

AI/ML, or related field. (PhD is valued but not mandatory.)

● 5+ years of direct, hands-on professional experience in the tech industry as an

AI/ML Eng

About Us

We are building transformer models focused on multilingual translation and custom transformer architectures. Our team works on large-scale NLP and transformer-based models with a strong focus on research, experimentation, model optimization, and production-grade AI systems.

We are looking for a highly technical Data Science Lead who can drive end-to-end model development, mentor engineers, and lead the evolution of our AI stack.

This is a core engineering and research role not a prompt engineering or API integration role.

Role Overview

As a Data Science Lead, you will lead the design, training, fine-tuning, evaluation, and optimization of transformer-based NLP systems and LLMs. You will work closely with engineering and research teams to build scalable AI models from the ground up and establish technical direction for the organization.

You should be comfortable working deeply with model internals, training pipelines, datasets, tokenization strategies, and distributed GPU-based training environments.

Key Responsibilities

• Lead the architecture and development of transformer-based AI systems
• Drive technical direction for NLP, LLM, and multilingual AI initiatives
• Mentor and guide junior ML engineers and researchers
• Train and fine-tune transformer models on large-scale custom datasets
• Work

Role : ITQ Data Scientist II

Skills : Gen AI/ AI Agents, AI/ML, Computer vision, LLM

Experience : 4 to 6 Years

Location : Mumbai (open for relocation)

Work mode :Hybrid

Key Responsibilities

Technical Excellence (70%)

• Lead full ML lifecycle: problem framing → data prep → modeling → deployment
• Build predictive models (regression, classification, clustering, time-series)
• Apply statistical and advanced analytics to structured & unstructured data
• Develop scalable ML pipelines and deploy models to production
• Design and implement AI agents using LLMs, RAG, memory, tools, and orchestration frameworks
• Evaluate and optimize AI systems using custom metrics and feedback loops
• Stay current with emerging ML and GenAI advancements

Business Partnership (15%)

• Translate business needs into analytical solutions
• Communicate insights clearly to technical and non-technical stakeholders
• Deliver projects on time with defined success criteria

Innovation & Continuous Improvement (10%)

• Improve processes and methodologies
• Develop new analytical capabilities
• Continuously upskill in ML and AI best practices

Administration (5%)

• Complete required trainings and organizational responsibilities

Interested candidates can share your CV to samban

YOU MUST APPLY HERE TO BE CONSIDERED: Application link:

Official JD + About us:

‍ YOUR ROLE

We're looking for a Senior Data Scientist who can build and optimize our AI models that power our voice AI platform. You'll be the brain behind our technology, ensuring our AI can handle complex conversations while maintaining high accuracy and natural-sounding interactions.

Your work will involve:

• Own end-to-end model development – from requirement gathering and algorithm design to implementation and deployment, you'll shepherd ML features through their complete lifecycle.
• Build for conversational intelligence – develop models that can handle hundreds of thousands of conversations per day with high accuracy and natural language understanding.
• Innovate through research – stay current with cutting-edge NLP and speech technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge.
• Design ML pipelines – create robust, scalable machine learning infrastructure that can continuously improve from our growing conversation data.
• Optimize for performance – identify and resolve model bottlenecks to ensure our voice AI delivers natural, real-time conversations without comprehension issues.


Arrowhead



4 days ago