Senior Data Scientist – Databricks, Pricing & Revenue Growth Management

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🕒 Outubro 20

🇦🇷 Argentina – Remoto

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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MUTT DATA

SiteLinkedInTodas as Vagas

51 - 200 funcionários

📣 Marketing

🛡️ Seguros

📦 Logística

Marketing • Insurance • Logistics

A MUTT DATA é uma empresa de consultoria especializada em alavancar a IA e o machine learning para criar sistemas automatizados que aumentam a receita de seus clientes. Eles oferecem soluções em setores como Adtech, Martech, Fintech e Telecomunicações, focando na otimização de plataformas de publicidade, aprimoramento de estratégias de marketing orientadas por dados e fornecimento de insights em tempo real nas redes financeiras e de telecomunicações. A MUTT DATA fornece aumento de equipe de especialistas, integração perfeita de arquiteturas de dados na nuvem e soluções sob medida para refinar estratégias de produto. Seus serviços incluem a implementação de pilhas modernas de dados, modelagem de mix de marketing e IA generativa. A MUTT DATA faz parcerias com empresas líderes como Amazon Web Services, Google Cloud, entre outras, para oferecer soluções avançadas de dados e IA. Eles são reconhecidos na América Latina por suas competências em AWS e expertise em ciência de dados e MLOps, garantindo sistemas de dados robustos, escaláveis e de custo-efetivo para seus clientes.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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

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