Job Title: Data Scientist – Revenue Growth Management

Location: Bangalore

Employment Type: Full-time

Experience: 3–6 Years

Industry Focus: IT Services, Artificial Intelligence & Analytics

Position Summary

We are looking for a skilled Data Scientist – Revenue Growth Management (RGM) with 3–6 years of experience in Data Science, Advanced Analytics, or Machine Learning. The ideal candidate will have strong hands-on expertise in developing advanced analytics and machine learning solutions across pricing, promotion effectiveness, demand forecasting, and trade spend optimization.

The role will focus on developing scalable, data-driven solutions for Consumer Packaged Goods (CPG), FMCG, and retail businesses, leveraging commercial datasets and advanced statistical and machine learning techniques. The ideal candidate will combine strong data science and engineering capabilities with an understanding of key commercial levers such as price elasticity, promotional uplift, cannibalization, trade investment, revenue, and margin.

The candidate will work closely with sales, marketing, finance, category, and commercial teams to translate analytical outputs into actionable recommendations and business decisions.

Strategic Responsibilities

- Develop pricing and price-elasticity models across products, customers, channels, regions, and markets.
- Build promotion effectiveness models to estimate baseline sales, incremental promotional uplift, cannibalization, halo impact, forward buying, and promotion ROI.
- Develop demand and sales forecasting models to support commercial planning and revenue growth initiatives.
- Create trade spend and promotional budget optimization solutions using statistical and mathematical optimization techniques.
- Run scenario simulations to assess the impact of changes in price, discount depth, promotion timing, promotion frequency, and budget allocation.
- Build scalable data pipelines and analytical workflows using Python, SQL, PySpark, and Databricks.
- Work with diverse commercial datasets, including sales, pricing, promotion, distribution, inventory, product, customer, and market data.
- Develop robust data science and machine learning models to support Revenue Growth Management initiatives.
- Apply statistical modelling, regression, forecasting, feature engineering, and model validation techniques to solve complex commercial problems.
- Translate model outputs and analytical findings into clear, actionable recommendations for sales, marketing, finance, category, and commercial stakeholders.
- Manage the model lifecycle using MLflow, model registries, deployment, monitoring, and retraining practices.
- Contribute to MLOps best practices, including model versioning, deployment automation, monitoring, and continuous improvement.
- Optimize analytical solutions for scalability, performance, and business impact.
- Collaborate with cross-functional business and technical teams to deliver production-ready data science solutions.
- Stay updated with emerging trends in advanced analytics, machine learning, optimization, and AI technologies relevant to commercial and RGM use cases.





Required Experience

- 3–6 years of professional experience in Data Science, Advanced Analytics, Machine Learning, or a related field.
- Strong hands-on experience with Python and SQL.
- Working knowledge of PySpark and large-scale data processing.
- Practical experience with Databricks, including notebooks, workflows/jobs, Delta Lake, and MLflow.
- Strong understanding of Machine Learning, statistics, regression, forecasting, feature engineering, and model validation.
- Experience in at least one of the following areas: Pricing Analytics, Promotion Effectiveness, Demand Forecasting, Revenue Growth Management (RGM), Commercial Analytics, or Statistical/Mathematical Optimization.
- Experience developing analytical models for business and commercial decision-making.
- Strong understanding of data preparation, statistical modelling, model evaluation, and optimization techniques.
- Experience working with structured commercial datasets such as pricing, sales, promotion, distribution, inventory, customer, product, and market data.
- Understanding of MLOps practices, including model versioning, deployment, monitoring, and retraining.
- Ability to communicate complex analytical findings and business recommendations effectively to both technical and business stakeholders.

Technical Skills

- Data Science & Machine Learning: Python, SQL, Machine Learning, Statistical Modelling, Regression, Forecasting, Feature Engineering, Model Validation, Optimization Techniques.
- Big Data & Data Engineering: PySpark, Large-scale Data Processing.
- Databricks & MLOps: Databricks, Databricks Notebooks, Databricks Workflows/Jobs, Delta Lake, MLflow, Model Registries, Model Deployment, Model Monitoring, Model Retraining.
- Cloud & AI Platforms: GCP or AWS.
- Revenue Growth Management & Commercial Analytics: Pricing Analytics, Price Elasticity, Promotion Effectiveness, Demand Forecasting, Trade Spend Optimization, Promotional Budget Optimization, Revenue Growth Management, Scenario Simulation, Promotion ROI.

Good to Have

- Experience working in CPG, FMCG, Retail, or Commercial Analytics.
- Exposure to causal inference, experimental design, A/B testing, or uplift modelling.
- Experience with advanced pricing and promotion analytics.
- Knowledge of trade spend optimization and commercial budget allocation.
- Exposure to Generative AI, Large Language Models (LLMs), or Agentic AI.
- Experience integrating analytical and machine learning models into APIs, applications, or decision-support platforms.
- Familiarity with cloud-native data science and machine learning architectures.
- Experience working with business stakeholders to translate complex analytical outputs into actionable commercial recommendations.





Educational Qualifications

- Bachelor's or Master's degree in Economics, Econometrics, Statistics, Data Science, Mathematics, Computer Science, or another quantitative discipline.
- Strong foundation in statistics, regression, hypothesis testing, time-series analysis, machine learning, and optimization is expected.

Soft Skills

- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to translate complex data science and analytical outputs into clear business recommendations.
- Ability to work effectively with cross-functional teams across sales, marketing, finance, category, commercial, product, and technology functions.
- Strong business acumen and understanding of commercial decision-making.
- Ability to work effectively in rapid-paced and agile environments.
- Strong ownership mindset with a focus on delivering scalable, high-impact data science solutions.
- Passion for continuous learning and innovation in Data Science, Advanced Analytics, and AI.
- Ability to manage multiple priorities and deliver high-quality work within defined timelines.
- Detail-oriented with a strong focus on analytical accuracy, business impact, and customer value.

About Polestar:

As a data analytics and enterprise planning powerhouse, Polestar Analytics helps its customers bring out the most sophisticated insights from their data in a value-oriented manner. From analytics foundation to analytics innovation initiatives, we offer a comprehensive range of services that help businesses succeed with data.

We have a geographic presence in the United States (Dallas, Manhattan, New York, Delaware), UK(London) & India (Delhi-NCR, Mumbai, Bangalore & Kolkata) and have 600+ people strong world-class team. We are growing at a rapid pace and plan to double our growth each year. This provides immense growth and learning opportunities for those who are choosing to work with Polestar.

We hire from most of the Premier Undergrad and MBA institutes. We are serving customers across 20+ countries. Our expertise and deep passion for what we do has brought us many accolades.

The list includes: -

- Recognized as the Top 50 Companies for Data Scientists in 2023 by AIM.
- Financial Times awarded Polestar as High-Growth Companies across Asia-Pacific for a 5th time in a row in 2023.
- Featured on the Economic Times India's Growth Champions in FY2023.
- Polestar Analytics Selected as a 2022 Red Herring Global Companies.
- Top Data Science Providers in India 2023: Penetration and Maturity (PeMa) Quadrant.
- India’s most promising data science companies in 2022 by Analytics Insight.
- Featured on Forrester's Now Tech: Customer Analytics Service Providers Report Q2, 2021.
- Recognized as Anaplan's India RSI Partner of the Year FY21.
- Elite Qlik Partner and a member of the ‘Qlik Partner Advisory Council’ & Microsoft Gold Partners for Data & Cloud Platforms Culture at Polestar.

We have one of the most progressive people’s practices which are all aimed at enabling fast paced growth for those who deserve it.

📌 Data Science Specialist (Bengaluru)
🏢 Polestar Analytics
📍 Bengaluru