Contractor Data Scientist (Price Elasticity & AI/ML)

Senior Data Scientist - Price Elasticity & AI/ML

Location: Anywhere in LATAM

Project: Retail & CPG AI Innovation

We are looking for a Senior Data Scientist with deep expertise in Price Elasticity to drive a high-impact innovation project for the retail and CPG industry.

In this role, you’ll design and validate AI/ML-powered prototypes that bring elasticity-driven insights into smarter pricing, promotions, and demand forecasting strategies.

What You’ll Be Doing:

• Model and measure price elasticity of demand across products, categories, and customer segments.
• Develop and test AI/ML models that incorporate elasticity coefficients into demand forecasting and pricing scenarios.
• Analyze structured and unstructured retail data to uncover trends and quantify customer sensitivity to price changes.
• Apply statistical, econometric, and causal inference techniques to simulate what-if pricing and promotion strategies.
• Build and iterate on prototypes and POCs that integrate elasticity insights into real-world retail/CPG contexts.
• Present findings through clear storytelling and data visualization, influencing both technical and business stakeholders.
• Collaborate with engineering and product teams to bring data-driven solutions into production.

What You Bring:

• Bachelors degree or higher in Econometrics, Operations Research, Applied Mathematics, Statistics, Data Science, or related field.
• 5+ years of experience in retail or CPG, with proven expertise in price elasticity modeling and demand forecasting.
• Strong command of Python (pandas, NumPy, OOP) and SQL.
• Demonstrated experience quantifying elasticity coefficients and applying them in business contexts.
• Solid background in regression models, time-series forecasting, and causal inference.
• Experience working with large, complex datasets and iterating prototypes in collaboration with cross-functional teams.
• Ability to communicate complex analytical insights in a way that resonates with both technical and non-technical audiences.
• Familiarity with scalable cloud environments and distributed data systems.

Nice to Have:

• Knowledge of scikit-learn, TensorFlow, PyTorch.
• Hands-on experience with Spark, Databricks, or similar big data platforms.
• UI prototyping skills (Flask, Plotly, Streamlit) to showcase elasticity models interactively.
• Understanding of CI/CD and modern ML Ops workflows.

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