Data Scientist Revenue Growth Management (CPG)

Job Description

Job Description

Data Scientist – Revenue Growth Management (Client)

• Location: Bay Area, CA
• Experience:3-5 years
• Employment Type: Contract – min 6 months
• GC and USC

Key Requirements:

• Job Summary
• We are seeking an experienced Senior Data Scientist with strong Consumer Packaged Goods (Client) industry experience, specifically in Revenue Growth Management (RGM). The ideal candidate will have a deep understanding of pricing strategies, promotional effectiveness, product assortment optimization, and the data-driven decisions that drive revenue growth and profitability.
• The candidate must possess strong hands-on expertise in Data Science, Machine Learning (ML), and Databricks, with the ability to develop, implement, and optimize advanced analytical models that support commercial decision-making. The role requires close collaboration with business and technical stakeholders to translate complex data into actionable insights.
• Key Responsibilities
• Develop and implement advanced Data Science and Machine Learning models to support Revenue Growth Management initiatives.
• Analyze and optimize pricing strategies, promotional effectiveness, product assortment, and revenue growth opportunities.
• Apply statistical modeling, predictive analytics, and machine learning techniques to improve pricing, demand forecasting, and promotional planning.
• Work with large and complex Client datasets to identify trends, consumer behavior patterns, pricing sensitivities, and growth opportunities.
• Utilize Databricks for data processing, analytical modeling, feature engineering, and ML model development.
• Build scalable analytical solutions to support pricing optimization, promotion planning, assortment decisions, and profitability improvement.
• Collaborate with business, commercial, and data engineering teams to translate business requirements into data-driven solutions.
• Evaluate model performance and communicate analytical findings and recommendations to stakeholders.
• Support the deployment, monitoring, and continuous improvement of ML models and analytical pipelines.
• Required Qualifications
• Strong experience in the Consumer Packaged Goods (Client) industry, specifically in Revenue Growth Management (RGM).
• Deep understanding of pricing, promotions, assortment optimization, and the underlying data used to make commercial decisions.
• Strong hands-on experience in Data Science, Machine Learning, statistical modeling, and predictive analytics.
• Practical experience with Databricks for data analysis, model development, and large-scale data processing.
• Proficiency in Python and relevant data science libraries, such as pandas, NumPy, scikit-learn, or similar tools.
• Experience working with large datasets and translating analytical results into actionable business recommendations.
• Strong problem-solving, analytical, and communication skills.
• Ability to work independently and collaborate with cross-functional teams.
• Working Hours
• Must be comfortable working during US business hours.
• Ability to collaborate with stakeholders across US time zones.
• Preferred Qualifications
• Experience with cloud-based data platforms and modern data engineering ecosystems.
• Knowledge of demand forecasting, price elasticity, trade promotion optimization, and commercial analytics.
• Experience deploying and monitoring machine learning models in production environments.
• Ideal Candidate Profile: A hands-on Data Scientist with proven Client and Revenue Growth Management experience, strong knowledge of pricing, promotions, and assortment, and practical Databricks and Machine Learning expertise