Data Scientist

Навыки

• A/B-тесты
• AI-инструменты в работе
• API (интеграции)
• Azure
• XGBoost / LightGBM / CatBoost
• CI/CD
• Решения на данных

О компании и продукте

• Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
• At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications are welcome and will be considered based on merit against the job and/or experience for the position.

Задачи

• As a Data Scientist – Pricing Automation & Optimization at Capgemini , you will design, develop, and deploy advanced machine learning and optimization solutions that drive pricing strategy, revenue growth, and business performance
• You will work closely with cross-functional teams and senior stakeholders to transform complex business challenges into scalable AI/ML solutions
• This role requires a strong foundation in data science, machine learning, experimentation, and optimization techniques, combined with the ability to communicate technical insights to both technical and business audiences
• You will contribute to strategic AI initiatives while delivering production-grade analytical solutions in cloud-based environments
• Responsibilities & Scope
• Develop and deploy end-to-end machine learning models for
• Pricing optimization
• Demand forecasting
• Price elasticity estimation
• Build, productionize, and maintain ML solutions using Azure ML , Databricks , and modern MLOps practices
• Implement prescriptive analytics and optimization techniques using
• Linear Programming
• Mixed Integer Programming (MIP)
• Reinforcement Learning
• Design, develop, and maintain feature stores, model monitoring processes, and model drift detection frameworks using MLflow
• Design and execute experiments, A/B testing initiatives, and quasi-experimental analyses to measure business impact and revenue improvements
• Collaborate closely with Data Engineering teams to establish data quality standards, data contracts, and scalable analytical solutions
• Support CI/CD and MLOps processes using Azure DevOps and cloud-native development practices
• Develop scalable API and batch-serving solutions for machine learning models
• Present insights, recommendations, risks, assumptions, and trade-offs to stakeholders through executive-level communications and data storytelling
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Требования

• Data-driven problem solver – Uses advanced analytics and machine learning to solve complex business challenges and generate measurable value
• AI/ML expertise – Strong understanding of predictive modeling, optimization methods, and machine learning lifecycle management
• Business-oriented mindset – Translates technical findings into meaningful business recommendations and actionable strategies
• Collaborative communicator – Effectively partners with technical teams, business leaders, and cross-functional stakeholders
• Continuous learner – Stays current with emerging AI, machine learning, and data science technologies and best practices
• Technical
• 2–4 years of hands-on experience delivering production-grade Data Science and Machine Learning solutions
• Strong proficiency in Python and machine learning libraries including
• Scikit-learn
• Hands-on experience with
• Delta Lake
• Azure Machine Learning
• Databricks
• Experience building, deploying, and monitoring machine learning models in cloud environments
• Strong understanding of
• Experimental Design
• Statistical Testing
• Hypothesis Testing
• Causal Inference fundamentals
• Experience implementing MLOps practices and model lifecycle management
• Ability to communicate technical concepts clearly to non-technical audiences
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• Provider
• Description
• SAP as service provider

Будет плюсом

• Experience with PyTorch or TensorFlow
• Knowledge of Revenue Management, Pricing, or Forecasting domains
• Experience with Reinforcement Learning and advanced optimization frameworks
• Familiarity with API development and model-serving architectures
• Exposure to Generative AI use cases and enterprise AI initiatives
• Job Description
• Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software
• Visualize, interpret, and report data findings
• May create dynamic data reports
• Job Description - Grade Specific
• The role combines advanced technical expertise in data science with consulting skills to provide strategic guidance and solutions to clients
• What you’ll love
• Exposure to top global companies working with Capgemini (145 of the Fortune 500 companies)
• Tech solutions and projects driving societal impact and paving the way for a sustainable future
• Well-being hub and different wellbeing initiatives
• Need to know
• Community Engagement: Participate in local volunteering initiatives, tech meetups, and cultural events that connect you with the Capgemini community
• Opportunities to work on cutting-edge AI, Machine Learning, and Data Science initiatives that directly influence strategic business decisions

Условия

• Career Development in Spanish & English: Training, certifications, and mentorship programs available in both languages to support bilingual growth

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