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Data Scientist (PriceElasticity/ML/PST) (Remote - Latam) at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Data Scientist (Price Elasticity/ML/PST). in . Latin America. .. In this role, you will leverage advanced data science techniques to analyze and model price sensitivity across retail and consumer goods markets. You will design and validate AI/ML-powered prototypes that improve pricing, promotions, and demand forecasting strategies. By combining econometric modeling, statistical analysis, and machine learning, your work will directly influence business decisions, enabling smarter revenue optimization and customer insights. This position offers the chance to work with large, complex datasets, collaborate with cross-functional teams, and translate technical results into actionable business recommendations. You will operate in a fully remote environment, contributing to high-impact projects in an innovative, fast-paced setting.. . Accountabilities. Model and measure price elasticity of demand across products, categories, and customer segments.. Develop, test, and iterate AI/ML models incorporating elasticity coefficients into demand forecasting and pricing strategies.. Analyze structured and unstructured retail data to identify trends and quantify consumer responses to price changes.. Apply statistical, econometric, and causal inference methods to simulate what-if scenarios for pricing and promotions.. Build prototypes and proofs-of-concept that integrate elasticity insights into real-world retail and CPG contexts.. Present findings through data storytelling and visualization, influencing both technical and business stakeholders.. Collaborate with engineering and product teams to implement data-driven solutions into production systems.. . Bachelor’s degree or higher in Econometrics, Operations Research, Applied Mathematics, Statistics, Data Science, or related fields.. 5+ years of experience in retail or consumer goods, with expertise in price elasticity modeling and demand forecasting.. Strong proficiency in Python (pandas, NumPy, OOP) and SQL.. Demonstrated experience quantifying elasticity coefficients and applying them to business decisions.. Solid understanding of regression models, time-series forecasting, and causal inference.. Experience working with large, complex datasets and iterating prototypes collaboratively.. Excellent communication skills to translate analytical insights to both technical and non-technical audiences.. Familiarity with scalable cloud environments and distributed data systems.. Bonus: experience with scikit-learn, TensorFlow, PyTorch, Spark, Databricks, or ML Ops workflows.. Bonus: UI prototyping skills using Flask, Plotly, or Streamlit for interactive model demonstration.. . Company Location: Argentina.