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Your RoleAs a MarTech Data Science Lead at Capgemini , you will serve as the senior technical authority responsible for shaping the vision, roadmap, methodologies, and delivery standards of the MarTech Data Science portfolio.
You will drive the development of advanced analytics, machine learning, experimentation, and AI solutions that improve customer experience, marketing performance, operational efficiency, and business growth. This role requires deep expertise in Data Science, technical leadership, model governance, and production Machine Learning environments.
You will partner with business and technology leaders to identify high-impact opportunities, guide technical decisions, establish best practices, and ensure analytical solutions generate measurable business value.
Responsibilities & ScopeData Science Strategy & VisionDefine and communicate the MarTech Data Science technical roadmap.
Identify and prioritize opportunities where advanced analytics and machine learning can drive measurable business outcomes.
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 LeadershipLead problem definition, solution design, methodology selection, and model architecture decisions.




Drive the development of:Predictive ModelsPrescriptive AnalyticsRecommendation EnginesCustomer Segmentation ModelsOptimization ModelsPropensity ModelsExperimentation FrameworksDefine success metrics and measurement strategies for analytical initiatives.
Guide teams through model validation, deployment, monitoring, and continuous improvement.
Experimentation & MeasurementEstablish frameworks for:A/B TestingIncrementality MeasurementHoldout DesignUplift AnalysisCausal InferenceExperimental DesignEnsure analytical rigor in evaluating marketing, customer, and operational initiatives.
Define standards for measuring business impact and ROI.
Model Governance & Responsible AIEstablish standards for:Model QualityReproducibilityDocumentationMonitoringValidationGovernanceLifecycle ManagementLead 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 & MentorshipServe 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 AdvisoryPartner 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 AIReview and guide MLOps architectures and production deployment strategies.
Support best practices for:CI/CDModel DeploymentMonitoringRetrainingEnvironment ManagementProduction SupportEnsure 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 SkillsRequired QualificationsBachelor's or Master's Degree in:Data ScienceStatisticsApplied MathematicsComputer ScienceEngineeringEconomicsOperations ResearchOr a related quantitative discipline.8-12+ years of experience in:Data ScienceMachine LearningAdvanced AnalyticsAI SolutionsMinimum 3 years of experience providing technical leadership for production Machine Learning teams.
Required SkillsApplied Data Science & StatisticsExpertise in:Predictive AnalyticsPrescriptive AnalyticsSegmentationRecommendation SystemsOptimizationCausal InferenceExperimental DesignDeep understanding

📌 Technical Program Lead (Aguascalientes)
🏢 Capgemini
📍 Aguascalientes