Manager, Data Science & AI

Job Description

Role Overview:At Visa, as a Manager in Data Science, you will play a crucial role in leveraging advanced analytics and AI to develop scalable business solutions that impact customer outcomes at scale. Your responsibilities will include end-to-end AI-driven analytics, from problem framing to model development, deployment, monitoring, and business adoption. You will be supporting Visas clients and internal stakeholders by driving insights, models, and recommendations that influence portfolio performance, customer lifecycle outcomes, and campaign effectiveness.Key Responsibilities:- Conduct deep-dive analysis on large-scale transactions and customer data to derive actionable business insights.- Build, validate, and interpret statistical and machine learning models such as propensity, segmentation, forecasting, and uplift.- Execute the entire analytics workflow including problem framing, data exploration, feature engineering, modeling, and validation.- Ensure analytical rigor, data quality checks, and quality assurance on all deliverables.- Translate analytical outputs into clear insights and recommendations for non-technical stakeholders.- Support the deployment of data science models into production environments in collaboration with engineering and platform teams.- Contribute to model monitoring, performance tracking, and periodic recalibration.- Utilize AI/ML techniques to enhance scalability, automation, or personalization use cases.- Design and support AI-enabled solutions like propensity engines, recommendation models, and campaign optimization tools.- Translate AI concepts into practical client use cases, addressing problem framing, value sizing, feasibility assessment, and adoption roadmap development.- Partner with technology, product, and governance teams to operationalize AI/ML solutions with appropriate controls, documentation, monitoring, and model risk considerations.- Apply responsible AI principles such as explainability, fairness, data governance in model design and delivery.- Create user-friendly dashboards, presentations, and executive-ready materials.- Manage multiple analytics projects simultaneously, ensuring timely delivery against the analytic plan.- Stay updated with evolving analytics, ML, and AI techniques relevant to payments and consumer data.- Evaluate new data sources, tools, and methodologies to enhance core data science outcomes.- Share best practices and learnings across teams and markets.Qualifications:Education & Experience- Bachelors degree in Economics, Finance, Computer Science, Statistics, or related quantitative field.- 6 years of hands-on experience in data science, analytics, and feature engineering.- Experience delivering analytics projects end-to-end in a fast-paced, client-facing environment.- Experience supporting/owning deployment of AI/ML models in real-world business contexts (production or pilot environments).Technical Skills- Strong proficiency in Python and data platforms (Hadoop, Hive, Impala, or cloud-based equivalents).- Solid understanding of statistical and ML techniques (regression, classification, clustering, tree-based models, etc.).- Familiarity with model deployment and ML lifecycle concepts is a plus.- Hands-on exposure to AI/ML lifecycle practices including feature stores, model registries, experiment tracking, CI/CD for models, monitoring, drift detection, and periodic recalibration.- Working knowledge of GenAI and LLM-enabled analytics use cases.- Ability to apply responsible AI practices including explainability, fairness, privacy, governance, and clear documentation of model assumptions and limitations.(Note: Any additional details about the company mentioned in the job description have been omitted.) Role Overview:At Visa, as a Manager in Data Science, you will play a crucial role in leveraging advanced analytics and AI to develop scalable business solutions that impact customer outcomes at scale. Your responsibilities will include end-to-end AI-driven analytics, from problem framing to model development, deployment, monitoring, and business adoption. You will be supporting Visas clients and internal stakeholders by driving insights, models, and recommendations that influence portfolio performance, customer lifecycle outcomes, and campaign effectiveness.Key Responsibilities:- Conduct deep-dive analysis on large-scale transactions and customer data to derive actionable business insights.- Build, validate, and interpret statistical and machine learning models such as propensity, segmentation, forecasting, and uplift.- Execute the entire analytics workflow including problem framing, data exploration, feature engineering, modeling, and validation.- Ensure analytical rigor, data quality checks, and quality assurance on all deliverables.- Translate analytical outputs into clear insights and recommendations for non-technical stakeholders.- Support the deployment of data science models into productio

Keyskills :
PythonStatistical ModelingMachine LearningData ScienceStakeholder ManagementDelivery ManagementInnovationContinuous ImprovementData PlatformsFeature EngineeringAIML DeploymentModel DeploymentData Quality ChecksAIML SolutioningModel Monito