Senior Data Scientist – Databricks, Pricing and Revenue Growth Management

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

📋 Description

• Create, enhance, and optimize sophisticated Pricing and Revenue Growth Management (RGM) models to facilitate strategic business decisions.

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

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

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

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

• Design and implement experiments, backtesting, sensitivity analyses, and statistical validations to ensure the reliability of models.

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

• Create pricing scenarios and simulations to evaluate the consequences of commercial strategies.

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

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

⛳️ Requirements

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

• Advanced skills in Python and SQL.

• In-depth knowledge of applied statistics, econometrics, and supervised Machine Learning.

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

• Strong comprehension of own-price and cross-price elasticity.

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

• Solid foundation in time series analysis and forecasting.

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

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

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

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

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

• Background in handling sales datasets that encompass pricing, volume, products, channels, geographies, and time dimensions.

• Capability to build models across various levels of granularity and evaluate their statistical robustness and stability over time.

• Strong analytical and problem-solving abilities, with the capacity to translate business challenges into mathematical and predictive models.

• Exceptional communication and data storytelling skills, with experience in presenting insights to both technical and business audiences.

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

🏝️ Benefits

• Remote-first culture – work from any location.

• Full coverage for AWS, DBT, Google Cloud, Azure & Databricks certifications.

• Birthday off plus an additional week of vacation (Mutt Week!).

• Referral bonuses.

• Maslow: Monthly credits for spending in our benefits marketplace.

• Annual Mutters' Trip.