Senior Data Scientist – Databricks, Pricing & Revenue Growth Management

Job not on LinkedIn

🔥 2 minutes ago

🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 19%

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MUTT DATA

WebsiteLinkedInAll Job Openings

51 - 200 employees

📣 Marketing

🛡️ Insurance

📦 Logistics

Marketing • Insurance • Logistics

MUTT DATA is a consulting firm that specializes in leveraging AI and machine learning to create automated systems that drive revenue for their clients. They offer solutions in sectors such as Adtech, Martech, Fintech, and Telecommunication, focusing on optimizing advertising platforms, enhancing data-driven marketing strategies, and providing real-time insights in financial and telecommunications networks. MUTT DATA provides expert team augmentation, seamless integration of data architectures in the cloud, and tailor-made solutions to refine product strategies. Their services include implementing modern data stacks, marketing mix modeling, and generative AI. MUTT DATA partners with leading companies like Amazon Web Services, Google Cloud, and others to deliver advanced data and AI solutions. They are recognized in LATAM for their AWS competencies and expertise in data science and MLOps, ensuring robust, scalable, and cost-effective data systems for their clients.

📋 Description

• 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

• 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

• 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