Data Science Manager-RGM

Tredence Inc.; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Tredence Inc. is seeking a Lead Data Scientist to drive Revenue Growth Management initiatives, solving complex business problems with data and delivering measurable revenue impact.

You will design and deploy predictive and optimization models for RGM use cases, lead end-to-end projects, mentor junior data scientists, and translate analytical findings into actionable recommendations for cross‑functional stakeholders.

Qualifications

• 8–12 years of experience in Data Science with demonstrated business impact.
• Strong programming skills in Python (pandas, scikit‑learn, statsmodels, etc) and SQL.
• 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, promotion analytics, and demand forecasting.

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.

Skills

Python

SQL

Machine learning

RGM

Pricing analytics

Demand forecasting

Education

BE / BTech / Master’s or PhD

Tools

Tableau

Power BI

matplotlib

OR-Tools

Gurobi

Job 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