Data Scientist (Regular / Mid)

CPGvision is a recognized leader in Trade Promotion Management (TPM), Trade Promotion Optimization (TPO), and Revenue Growth Management (RGM). Leveraging the power of the Salesforce platform, they enable consumer goods companies to achieve their RGM objectives through a fully integrated, user-friendly solution suite.

The Data Science team builds scalable machine learning models that power advanced analytics for the CPG and Retail industries, helping global brands optimize pricing and promotional strategies by forecasting sales volume, measuring promotion effectiveness, and analyzing price elasticity of demand.

• Degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field.
• Minimum 1 year of commercial experience as a Data Scientist or Machine Learning Engineer.
• Proficiency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, statsmodels).
• Hands-on experience with gradient boosting models.
• Solid understanding of time-series forecasting, regression modeling, and cross-validation techniques.
• Knowledge of regression evaluation metrics in business contexts (e.g. MAE, R-squared, NRMSE).
• Experience with version control systems (Git) and clean, modular coding practices (OOP).
• Proficiency in SQL.
• Comfortable working in a Linux environment.
• Ability to present and communicate results to both technical and business stakeholders.
• Communicative English sufficient for reading documentation and presenting results.

Nice to have:

• Familiarity with CPG/FMCG or Retail data and domain-specific metrics.
• Experience with cloud environments, preferably AWS.
• Practical use of Explainable AI tools (e.g. SHAP).
• Experience with hyperparameter optimization frameworks (e.g. Optuna).
• Working knowledge of Excel for ad-hoc data analysis and reporting.

• Build and improve sales volume forecasting models using gradient boosting methods and regression techniques, including hyperparameter optimization.
• Explore and prepare data for modeling, including time-series feature creation, promotion and pricing analysis, outlier detection, and data quality assurance.
• Operationalize models and work within a production-grade ML pipeline leveraging cloud infrastructure.
• Collaborate with business teams to interpret and communicate model outputs, translating analytical results into actionable business insights.
• Test new hypotheses, evaluate alternative loss functions and algorithms, and explore improvements to existing modeling approaches.
• Pursue independent research topics with the opportunity to publish findings of novel scientific value.

PSignite is an Equal Opportunity, Affirmative Action employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply.