Senior Data Scientist – Databricks, Pricing & Revenue Growth Management

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Design, develop, and refine sophisticated Pricing and Revenue Growth Management (RGM) models to facilitate strategic business decisions.

• Construct and validate price-demand elasticity models, encompassing both own-price and cross-price elasticities.

• Create predictive models utilizing Machine Learning, statistical methodologies, and econometric techniques to examine demand, pricing, and consumer behavior.

• Conduct time series analysis, demand forecasting, and mathematical optimization to uncover business opportunities.

• Execute feature engineering leveraging pricing, sales volume, seasonality, product, channel, and market data.

• Design and implement experiments, backtesting, sensitivity analyses, and statistical validations to confirm model reliability.

• Assess model robustness, temporal consistency, potential biases, and the foundational statistical assumptions.

• Generate pricing scenarios and simulations to evaluate the effects of commercial strategies.

• Collaborate with business stakeholders, Data Engineers, and Machine Learning Engineers to convert business challenges into data-driven solutions.

• Convey complex analytical results and actionable recommendations to both technical and non-technical stakeholders.

⛳️ Requirements

• 4+ years of experience as a Data Scientist, preferably focused on Pricing, Revenue Growth Management (RGM), demand modeling, forecasting, or optimization.

• Advanced expertise in Python and SQL.

• Strong understanding of applied statistics, econometrics, and supervised Machine Learning.

• Practical experience with price elasticity modeling, demand modeling, price-response curves, or similar methodologies.

• Solid grasp of own-price and cross-price elasticity concepts.

• Familiarity with regression models, regularization methods, and statistical inference.

• Strong foundation in time series analysis and forecasting techniques.

• Experience with mathematical optimization, scenario modeling, and sensitivity analysis.

• Proficient in feature engineering using pricing, volume, seasonality, and commercial data.

• Experience in designing experiments, conducting backtesting, and performing statistical validation.

• Hands-on experience with Databricks, Spark/PySpark, and MLflow.

• Experience in developing and validating statistical and Machine Learning models that aid in business decision-making.

• Experience working with sales datasets that involve pricing, volume, products, channels, geographies, and time dimensions.

• Ability to construct models across various levels of granularity and evaluate their statistical robustness and temporal stability.

• Strong analytical and problem-solving abilities, with a knack for translating business challenges into mathematical and predictive models.

• Excellent communication and data storytelling capabilities, with a background in presenting insights to both technical and business audiences.

• Experience collaborating with cross-functional teams, including business stakeholders, Data Engineers, and Machine Learning Engineers.

• Nice-to-have: Experience with Large Language Models (LLMs).

• Nice-to-have: Familiarity with AI agents and agentic systems.

• Nice-to-have: Knowledge of MLOps practices and tools.

• Nice-to-have: Experience in deploying and maintaining Data Science and AI solutions in production settings.

• Nice-to-have: Understanding of job orchestration, computing infrastructure, deployments, monitoring, and maintenance.

• Nice-to-have: Experience working with event data, user tracking, and application tagging.

• Nice-to-have: Ability to effectively collaborate with Product, Engineering, and Business teams.

🏝️ Benefits

• Remote-first culture – work from anywhere.

• In-Company English Lessons.

• Wellhub or sports club stipend.

• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered.

• Food credits via Pedidos Ya.

• Birthday off + an extra vacation week (Mutt Week).

• Referral bonuses.

• Annual Mutters' Trip.

• Monthly Childcare Reimbursement.