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.

Requirements

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.

Benefits

Contractor agreement with payment in USD.
Fully remote work across Latin America.
Observance of local public holidays.
English classes and professional development resources.
Referral program and access to learning platforms.
Opportunity to work on high-impact, innovative AI/ML projects in retail and consumer goods.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

This process is transparent, skills-based, and free of bias, focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company offering the position. The final decision and next steps (such as interviews or assessments) are made by their internal hiring team.

Thank you for your interest!

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