Tredence Inc.
Website:
tredence.com
Job details:
Role description
Lead Data Scientist – Revenue Growth Management
We are looking for a Lead Data Scientist with strong expertise in solving complex business problems using data, with a specific focus on Revenue Growth Management (RGM). The ideal candidate will have deep hands-on experience in classical machine learning, pricing analytics, and demand forecasting, along with the ability to drive measurable revenue and margin impact. You will work closely with cross-functional teams including business, consulting, and engineering stakeholders to deliver data-driven strategies.
Key Responsibilities:
● Design, build, and deploy predictive and optimization models for RGM use cases such as price optimization, promotion effectiveness, and demand forecasting
● Translate business problems into analytical frameworks and provide actionable recommendations to improve revenue and profitability
● Develop model workflows using Python and SQL
● Apply statistical modeling and machine learning techniques for price elasticity estimation, uplift modeling, and forecasting
● Collaborate with cross-functional teams to integrate models into business processes and decision-making
● Present insights to stakeholders using data storytelling and visualization techniques
● Lead end-to-end project delivery and mentor junior data scientists
Required Skills and Experience:
● 8–12 years of experience in Data Science or Advanced Analytics with demonstrated business impact
● Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc)
● Proficiency in SQL for data extraction and transformation
● Deep understanding of classical machine learning techniques
(regression, classification, clustering, time series forecasting, optimization)
● Strong hands-on experience in Revenue Growth Management (RGM), including:
○ Pricing Analytics / Price Elasticity Modeling
○ Promotion Analytics / Trade Promotion Effectiveness
○ Demand Forecasting / Volume Forecasting
● Strong foundation in statistics, hypothesis testing, and quantitative problem-solving
Preferred Qualifications:
● BE / BTech / Master’s or PhD in Computer Science, Statistics, Economics, Operations Research, or related field
● Experience in FMCG / Retail / CPG domain is highly preferred
● Exposure to assortment optimization and portfolio analytics
● Experience with optimization techniques/tools (e.g., linear programming, OR-Tools, Gurobi)
● Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib)
● Experience in deploying and monitoring models in production environments
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