Senior Data Scientist – Databricks, Pricing & Revenue Growth Management
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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates advanced capabilities in Pricing and Revenue Growth Management through the development of predictive models and price-demand elasticity analysis. Proficient in statistical methods, machine learning, and effective communication of analytical insights to diverse stakeholders.
Highest-signal resume keywords
Advanced Proficiency In PythonStrong Knowledge Of Applied StatisticsExperience With Price Elasticity ModelingHands-On Experience With DatabricksStrong Analytical And Problem-Solving Skills
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design, develop, and optimize advanced Pricing and Revenue Growth Management (RGM) models to support strategic business decisions
- Build and validate price-demand elasticity models, including own-price and cross-price elasticities
- Develop predictive models using Machine Learning, statistical methods, and econometric techniques to analyze demand, pricing, and consumer behavior
- Perform time series analysis, demand forecasting, and mathematical optimization to identify business opportunities
- Conduct feature engineering using pricing, sales volume, seasonality, product, channel, and market data
- Design and execute experiments, backtesting, sensitivity analyses, and statistical validations to ensure model reliability
- Evaluate model robustness, temporal stability, potential biases, and underlying statistical assumptions
- Develop pricing scenarios and simulations to assess the impact of commercial strategies
- Collaborate with business stakeholders, Data Engineers, and Machine Learning Engineers to translate business challenges into data-driven solutions
- Communicate complex analytical findings and actionable recommendations to technical and non-technical stakeholders
Requirements
What you’ll need- 4+ years of experience as a Data Scientist, ideally working on Pricing, Revenue Growth Management (RGM), demand modeling, forecasting, or optimization
- Advanced proficiency in Python and SQL
- Strong knowledge of applied statistics, econometrics, and supervised Machine Learning
- Hands-on experience with price elasticity modeling, demand modeling, price-response curves, or equivalent approaches
- Solid understanding of own-price and cross-price elasticity
- Experience with regression models, regularization techniques, and statistical inference
- Strong background in time series analysis and forecasting
- Experience with mathematical optimization, scenario modeling, and sensitivity analysis
- Proficiency in feature engineering using pricing, volume, seasonality, and commercial variables
- Experience designing experiments, performing backtesting, and conducting statistical validation
- Hands-on experience with Databricks, Spark/PySpark, and MLflow
- Experience developing and validating statistical and Machine Learning models that support business decision-making
- Experience working with sales datasets involving pricing, volume, products, channels, geographies, and time dimensions
- Ability to build models across multiple levels of granularity and assess their statistical robustness and stability over time
- Strong analytical and problem-solving skills, with the ability to translate business challenges into mathematical and predictive models
- Excellent communication and data storytelling skills, with experience presenting insights to technical and business stakeholders
- Experience collaborating with cross-functional teams, including business stakeholders, Data Engineers, and Machine Learning Engineers
- Nice-to-have: Experience working with Large Language Models (LLMs)
- Nice-to-have: Knowledge of AI agents and agentic systems
- Nice-to-have: Familiarity with MLOps practices and tools
- Nice-to-have: Experience deploying and maintaining Data Science and AI solutions in production environments
- Nice-to-have: Knowledge 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 collaborate effectively with Product, Engineering, and Business teams
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical MethodsEconometric TechniquesTime Series AnalysisDemand ForecastingMathematical OptimizationFeature EngineeringRegression ModelsSensitivity AnalysisStatistical Validation
Soft Skills
Excellent Communication SkillsData Storytelling SkillsCollaboration Skills
Tools & Technologies
SQLDatabricksSpark/PySparkMLflow
Industry Keywords
PricingRevenue Growth ManagementDemand ModelingForecastingCommercial Strategies