Мексика#1 - Senior Data Scientist - Databricks - Pricing & Revenue Growth Management
вчера
МексикаSeniorRemote
machine learningstatisticseconometricspredictive modeling
Senior Data Scientist responsible for designing advanced Pricing and Revenue Growth Management models using ML and statistics.
О компании
- 🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀 At , we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning. This opportunity is with a leading multinational beverage company based in Mexico City. We are looking for a Senior Data Scientist to join our team 🐶🚀. You'll be responsible for designing, developing, and enhancing advanced Pricing and Revenue Growth Management (RGM) models , turning data on demand, pricing, product portfolios, sales channels, and consumer behavior into actionable insights that drive strategic business decisions. In this role, you'll combine Machine Learning, statistics, econometrics, and business expertise to build predictive models, analyze price-demand relationships, estimate price elasticities, and optimize pricing strategies. You'll work closely with business stakeholders, Data Engineers, and Machine Learning Engineers to develop scalable, statistically robust solutions that support commercial decision-making. Strong analytical thinking, business understanding, and the ability to translate complex data into actionable recommendations are essential to succeed in this collaborative environment.
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
Обязанности
- 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 both technical and non-technical stakeholders.
Будет плюсом
- Experience working with Large Language Models (LLMs).
- Knowledge of AI agents and agentic systems.
- Familiarity with MLOps practices and tools.
- Experience deploying and maintaining Data Science and AI solutions in production environments.
- Knowledge of job orchestration, computing infrastructure, deployments, monitoring, and maintenance.
- Experience working with event data, user tracking, and application tagging.
- Ability to collaborate effectively with Product, Engineering, and Business teams.
Условия
- Remote-first culture – work from anywhere! 🌍
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- Birthday off + an extra vacation week (Mutt Week! 🏖️)
- Referral bonuses – help us grow the team & get rewarded!
- Maslow : Monthly credits to spend in our benefits marketplace.
- ✈️ 🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
Другое
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
- Amazon Web Services
- Astronomer
- Databricks
- 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.