Job Description
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, we enable consumer goods companies to achieve their RGM objectives through our fully integrated, user-friendly solution suite.
About the Team
Our Data Science team builds scalable machine learning models that power advanced analytics for the CPG and Retail industries. We help global brands optimize their pricing and promotional strategies by forecasting sales volume, measuring promotion effectiveness, and analyzing price elasticity of demand.
We are looking for a Regular/Mid Data Scientist to join us in developing and deploying analytical models, working with real market challenges and large-scale sales data.
Work Mode
Fully remote. On-site collaboration 2-3 days per quarter.
Key Responsibilities
- Predictive Modeling: Build and improve sales volume forecasting models using gradient boosting methods and regression techniques, including hyperparameter optimization.
- Data Analysis & Feature Engineering: Explore and prepare data for modeling, including time-series feature creation, promotion and pricing analysis, outlier detection, and data quality assurance.
- MLOps: Operationalize models and work within a production-grade ML pipeline leveraging cloud infrastructure.
- Explainable AI (XAI): Collaborate with business teams to interpret and communicate model outputs, translating analytical results into actionable business insights.
- Research: 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.
You Must Have
- A 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 of your work to both technical and business stakeholders, translating model outcomes into clear business value.
- 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.
What We Offer
- Choice of employment contract or B2B.
- Fully remote work with quarterly on-site meetups (2-3 days).
- Work with large, compelling analytical datasets and real impact on decisions of major corporations.
- A structured research process from exploration through to production deployment.
- Access to cloud computing infrastructure and a modern technology stack.
- Opportunity to conduct independent research and publish results of scientific value.
- Mentorship support.
- Multisport card.
- Private medical care.
PSignite invests in the development of its employees. We are committed and aspire to leverage the qualities and appreciate each person's unique competencies to bring to our company. We are an Equal Opportunity, Affirmative Action employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply.