About Valiance
Valiance is a deep-tech AI company building mission-critical solutions for global enterprises across CPG, retail, manufacturing, and the public sector. As a Google Cloud and NVIDIA partner, we specialize in deploying scalable AI systems for predictive analytics, demand forecasting, and intelligent automation.
Role Overview
We are looking for an experienced Data Scientist with hands-on expertise in Revenue Growth Management (RGM) for CPG clients—spanning Promotion Planning, Promo Recommendation, Pricing, and Price Elasticity Modeling . The ideal candidate should have strong technical and analytical skills, experience implementing data science solutions in enterprise environments, and comfort working with clients to translate insights into actionable business outcomes.
Key Responsibilities
- Design and implement RGM models for promotion optimization, pricing recommendation, and elasticity measurement .
- Build and deploy Log-Log Linear and Constrained Linear Regression models to evaluate promo effectiveness and simulate scenarios.
- Collaborate with product and engineering teams to integrate models into production systems (preferably on o9 platform ).
- Conduct in-depth data analysis using Python and SQL to extract actionable insights on pricing and promotional strategies.
- Debug, tune, and optimize model performance for scalability and interpretability.
- Work closely with client stakeholders to explain model results , validate outputs, and ensure alignment with business objectives.
- Support end-to-end product implementation – from data ingestion and model design to deployment and monitoring.
Required Skills & Experience
4–7 years of hands-on experience in Data Science / RGM Analytics within CPG / Retail domains.Strong understanding of Revenue Growth Management (RGM) levers – promotion, pricing, trade spend, and assortment optimization .Proven experience building Promo Recommendation and Price Elasticity models.Proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels) and SQL for data manipulation and analysis.Experience with o9 platform or similar IBP / Demand Planning platforms preferred.Solid grounding in Log-Log Linear Regression , Constrained Linear Regression , and related econometric techniques.Strong analytical, debugging, and problem-solving skills.Excellent communication and client-handling abilities to present insights to business and technical stakeholders.Preferred Qualifications
Master’s or Bachelor’s degree in Statistics, Data Science, Economics, or Engineering .Experience with large-scale data systems and integration into production environments.Exposure to CPG trade promotion planning tools or pricing optimization systems is a plus