Data Scientist

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

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.
• Apply model interpretability techniques such as SHAP and LIME to explain model outputs and support business decision-making.
• 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.

Your Profile

• 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 Requirements

• 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
• XGBoost
• Hands-on experience with:
• Spark
• Delta Lake
• SQL
• Azure Machine Learning
• Databricks
• MLflow
• 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.

Nice to Have

• 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.

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

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

About Capgemini

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.