Establish long-term strategies for analytics, experimentation, machine learning, and AI initiatives.
Align Data Science investments with business objectives and enterprise priorities.
Advanced Analytics & Machine Learning Leadership
Lead problem definition, solution design, methodology selection, and model architecture decisions.
Drive the development of
Predictive Models
Prescriptive Analytics
Recommendation Engines
Customer Segmentation Models
Optimization Models
Propensity Models
Experimentation Frameworks
Define success metrics and measurement strategies for analytical initiatives.
Guide teams through model validation, deployment, monitoring, and continuous improvement.
Experimentation & Measurement
Establish frameworks for
A/B Testing
Incrementality Measurement
Holdout Design
Uplift Analysis
Causal Inference
Experimental Design
Ensure analytical rigor in evaluating marketing, customer, and operational initiatives.
Define standards for measuring business impact and ROI.
Model Governance & Responsible AI
Establish standards for
Model Quality
Reproducibility
Documentation
Monitoring
Validation
Governance
Lifecycle Management
Lead the implementation of Responsible AI practices across Data Science initiatives.
Define governance controls that promote transparency, accountability, explainability, and compliance.
Strengthen model QA processes and model-risk management practices.
Technical Leadership & Mentorship
Serve as the senior technical advisor for the Data Science team.
Guide architectural decisions and resolve complex technical challenges.
Mentor Data Scientists and Analytics professionals.
Promote peer reviews, knowledge sharing, and continuous improvement.
Foster a culture of innovation, scientific rigor, and business impact.
Stakeholder Engagement & Executive Advisory
Partner with Product, Marketing, Sales, Analytics, Data Engineering, MLOps, and Technology leaders.
Translate sophisticated analytical approaches and technical risks into clear executive recommendations.
Influence strategic decision-making through data-driven insights.
Present results and recommendations to senior leadership and executive audiences.
MLOps & Production AI
Review and guide MLOps architectures and production deployment strategies.
Support best practices for
CI/CD
Model Deployment
Monitoring
Retraining
Environment Management
Production Support
Ensure AI and ML solutions are scalable, maintainable, and production-ready.
Your Profile
Thought leader in Data Science – Passionate about leveraging analytics and AI to solve complex business problems.
Strategic advisor – Connects advanced analytics initiatives to measurable business outcomes.
Technical expert – Comfortable leading enterprise-scale machine learning and AI programs.
Influential communicator – Able to engage technical teams and executive stakeholders alike.
Mentor and coach – Invested in developing talent and fostering technical excellence.
Innovative problem solver – Combines scientific rigor with practical business thinking.
Qualifications & Preferred Skills
Required Qualifications
Bachelor's or Master's Degree in
Data Science
Statistics
Applied Mathematics
Computer Science
Engineering
Economics
Operations Research
Or a related quantitative discipline.
8-12+ years of experience in
Data Science
Machine Learning
Advanced Analytics
AI Solutions
Minimum 3 years of experience providing technical leadership for production Machine Learning teams.
Required Skills
Applied Data Science & Statistics
Expertise in
Predictive Analytics
Prescriptive Analytics
Segmentation
Recommendation Systems
Optimization
Causal Inference
Experimental Design
Deep understanding of statistical modeling and business-driven analytics.
Technical Leadership
Proven ability to influence technical direction and business decisions.
Experience mentoring Data Scientists and leading technical reviews.
Strong stakeholder management and executive communication capabilities.
Programming & Analytics Engineering
Advanced proficiency in
Python
SQL
Ability to review and contribute to production-grade analytical code.
Experience building scalable analytical solutions.
Cloud Analytics & Data Platforms
Strong experience with
Snowflake
Cloud-Based Machine Learning Platforms
Enterprise Data Platforms
Experience with Databricks, Apache Spark, or equivalent technologies is highly desirable.
Experimentation & Causal Measurement
Expertise in
A/B Testing
Incrementality Analysis
Holdouts
Lift Measurement
Causal Modeling
Ability to design measurement frameworks that demonstrate business value.
MLOps & Lifecycle Management
Understanding of
GitHub
CI/CD
Model Deployment
Monitoring
Retraining
Production ML Environments
Familiarity with model lifecycle governance and operational best practices.
Responsible AI
Experience defining AI governance frameworks and validation standards.
Ability to create guardrails that support ethical, transparent, and accountable AI implementation.
Preferred Skills
Marketing Analytics.
Customer Analytics.
Sales Analytics.
Customer Lifetime Value (CLV) Modeling.
Recommendation Systems and Personalization Engines.
Marketing Mix Modeling.
Propensity Modeling.
Snowflake Cortex.
Snowpark ML.
Model Risk Management Frameworks.
Enterprise AI Governance Programs.
What You'll Love
Opportunity to lead enterprise-scale Data Science and AI initiatives.
Exposure to cutting-edge Machine Learning, Advanced Analytics, and Responsible AI programs.
Collaboration with global Product, Data, Analytics, and Technology leaders.
Access to industry-leading certifications, technical academies, and leadership development programs.
Career growth opportunities within Capgemini's global Data & AI practice.
Inclusive and innovative environment focused on continuous learning and measurable business impact.
Need to Know
Career Development in Spanish & English: Access to technical certifications, mentorship programs, leadership development tracks, and continuous learning opportunities focused on AI, Machine Learning, Analytics, and Data Science.
Community Engagement: Participate in innovation challenges, AI communities, technical forums, knowledge-sharing sessions, volunteering initiatives, and global Capgemini events.
About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse organization with more than 340,000 team members in over 50 countries.
With more than 55 years of heritage, Capgemini helps clients unlock the value of technology through end-to-end services and solutions, leveraging capabilities in strategy and design, engineering, AI, generative AI, cloud, and data, combined with deep industry expertise and a strong partner ecosystem.
At Capgemini Mexico, we are committed to fostering a diverse and inclusive workplace where everyone has equal opportunities. We welcome applications from all qualified candidates and evaluate them based on merit, skills, qualifications, and experience relevant to the role.
Ref. code
588710
Posted on
Nov 3, 2026
Experience Level
Experienced Professionals
Contract Type
Permanent
Location
Aguascalientes, MX
Brand
Capgemini
Professional Community
Data & AI
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