Top Data & Analytics Jobs

Develop causal economic analyses using Mastercard and public datasets. Translate business questions into identification strategies, build econometric and causal machine-learning models, lead projects from data ingestion through validation, and communicate findings to clients and stakeholders. Guide best practices, prototype scalable analytics, conduct research, and apply experimentation methods across business contexts.

Develop causal economic analyses using Mastercard and public datasets to assess business decisions, market changes, events, and external shocks. Translate business questions into empirical designs, lead projects from data ingestion through model validation, prototype scalable causal inference methods, guide best practices, and communicate findings to internal and external stakeholders. The role requires econometric and causal machine-learning expertise, experimentation experience, and strong technical communication skills.

Leads People Analytics enablement and BI strategy, overseeing semantic models, certified data products, metric governance, data foundations, advanced analytics enablement, demand prioritization, and adoption. Partners with People Analytics, IT, and HR Strategy teams to create trusted workforce data, reusable semantic assets, and decision-ready insights. Manages teams and operating models while driving data quality, governance, certification, self-service analytics, AI access, and scalable insight delivery across the enterprise.

Designs and maintains data pipelines supporting monthly profitability close, automates manual finance workflows, and develops machine learning solutions for quality control, anomaly detection, and reconciliations. The role extracts and delivers financial data, prototypes LLM and agentic tools, and partners with Finance, Technology, and P&A on analytics initiatives. It also communicates technical methods and results to senior business stakeholders.

Leads the technical vision, architecture, and delivery of enterprise search analytics and ontology solutions for ecommerce. Manages and mentors software engineering teams, integrates platforms, oversees IT service operations and quality, and improves search relevance using NLP, vector search, personalization, machine learning, and performance KPIs. Partners with product, data science, and engineering leaders while driving ontology, metadata, governance, and semantic search adoption across digital commerce.

Leads global network economics and value optimization initiatives through data-driven pricing, interchange, revenue, and profitability analysis. Develops predictive models, simulations, segmentation frameworks, reporting, visualizations, data pipelines, and scalable analytics tools using large datasets. Partners with global and regional pricing teams, translates stakeholder needs into analytical solutions, presents actionable findings, manages project delivery, and mentors junior colleagues.

Develop and enhance data analytics solutions for Internal Audit, including automated testing, continuous monitoring, dashboards, reporting, risk analysis, and anomaly detection. Partner with audit teams, data owners, and stakeholders to analyze complex data, document procedures and findings, improve audit processes, and evaluate responsible applications of AI, machine learning, and automation.

Analyze business data, uncover operational improvement opportunities, and develop automation and self-service solutions. The role partners with stakeholders and subject matter experts, performs ad hoc analysis, communicates actionable insights, and leads simplification projects. It requires experience with analytics and automation tools including Alteryx, Tableau, SAS, SQL, Python, Snowflake, AWS, APIs, and AI/ML concepts. This is an onsite role five days per week and does not offer visa sponsorship.

Leads a global organization spanning data science, data architecture and engineering, and reporting and insights. Develops enterprise data strategy, oversees data products and analytics initiatives, advances predictive and prescriptive insights, establishes governance and quality standards, and partners with executives to deliver measurable business value. Builds high-performing teams, develops leaders, prioritizes investments, and drives scalable, trusted, decision-oriented analytics capabilities.

Designs and optimizes Snowflake data pipelines for clinical and claims data supporting HEDIS processing, quality analytics, chart abstraction, and care gap identification. Integrates AI, machine learning, and NLP models into healthcare data workflows; implements data quality, governance, security, and HIPAA-compliant practices. Partners with clinical quality and reporting teams to translate HEDIS specifications into automated solutions, while mentoring engineers and advancing MLOps and DataOps practices.

Build predictive models and customer economics analyses that forecast behavior, optimize marketing investments, and support revenue growth. Develop automated tools, dashboards, and repeatable frameworks to communicate customer performance and retention trends. Partner with Marketing, Finance, Data Science, and Data Engineering to translate complex model outputs into actionable business strategies using technologies including Databricks, Airflow, Bitbucket, SQL, and Snowflake.

Build predictive models forecasting customer behavior, analyze retention and gameplay trends, and create automated tools, analyses, and dashboards. Translate model outputs into actionable recommendations that guide marketing investments, promotional strategies, customer valuation, and retention. Partner with Marketing, Finance, Data Science, and Data Engineering teams while using Databricks, Airflow, Bitbucket, SQL, Snowflake, and dashboarding tools to support revenue growth and customer insights.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Leads enterprise competitive intelligence capabilities, including data collection, matching, scraping, governance, quality standards, analytical methodologies, and AI-enabled workflows. Partners with Product, Engineering, Data Science, Merchandising, Pricing, Digital, Marketplace, and Strategy teams to translate business needs into scalable solutions. Develops metrics, models, validation processes, and insights that support business decisions, while potentially managing and developing a small analytics team.

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Leads the design and modernization of scalable data architecture for economic data platforms, including massive time-series datasets, archival documents, and research publications. Responsibilities include data modeling, metadata and governance design, storage and processing architecture, indexing, discoverability, security, lifecycle management, and API data access optimization. Partners with application architecture and cross-functional teams to deliver highly available, secure, public-facing data platforms supporting analytics and research.

Lead statistical measurement and client intelligence initiatives using healthcare, prescription, and claims data. Develop performance benchmarks, evaluate program impact, apply statistical and machine learning methods, advise data scientists, support survey-based measurement, manage analytics vendors, mentor analysts, and present findings to marketing teams and clients. The role requires advanced SQL and Python, healthcare data expertise, vendor management, and extensive quantitative experience.

Own and advance the enterprise commercial data strategy across Sales, Insights & Analytics, Customer Experience, and related functions. Develop the data roadmap, evaluate and govern syndicated, retail, shopper, brand, and e-commerce data assets, and manage vendor contracts and performance. Lead data quality, regional support, and cross-functional alignment while piloting AI and machine learning capabilities for commercial data workflows.

Build and operate shared data services, platforms, and tooling supporting analytics and AI. Responsibilities include data ingestion and processing, reusable datasets, data quality, access management, automation, reliability, and collaboration with product and research teams. The 18-month Launch Program provides cross-functional experience and structured development for early-career professionals.

Monitor fraud trends in retail deposit acquisition, analyze large datasets, identify defensive gaps, and develop strategies balancing fraud losses, operational costs, and customer impact. Partner with cross-functional and technical product teams to deliver fraud prevention capabilities, present actionable insights to senior leadership, and support business growth while protecting customers.

Lead Data Architect responsible for defining and evolving data architecture and standards across 100+ applications, driving adoption of strategic data lake platforms, designing target-state architectures and data exchange patterns, mentoring junior architects, and ensuring governance, data quality, and cloud-based database best practices.

Develops automation, data pipelines, databases, analytics, machine learning models, reporting tools, and web applications for package technology quality assurance. Analyzes manufacturing, product, and reliability data to support risk assessment and root-cause investigations. Collaborates with engineering teams, communicates findings, trains users, maintains software and reports, and shares analytics best practices across global teams.

Design, build, deploy, and support scalable cloud data platforms, pipelines, and applications for risk management. Lead technical direction across data engineering, analytics, and machine learning teams; establish reusable engineering patterns; implement security and privacy controls; and collaborate with product managers and software engineers. The role includes mentoring, stakeholder communication, distributed data processing, data modeling, warehousing, streaming, and both relational and NoSQL database solutions.

Leads large-scale data engineering initiatives for Risk Tech, designing and delivering scalable cloud data platforms, pipelines, and applications. Responsibilities include architecture, data modeling, distributed processing, cloud warehousing, AI-enabled risk solutions, platform evaluation, operational resilience, and technical mentoring. The role collaborates with product managers, software engineers, analysts, and data scientists while independently driving architectural decisions and communicating technical outcomes to stakeholders.

Designs and leads scalable batch and real-time data pipelines supporting AI/ML applications, LLMs, RAG workflows, predictive models, and executive data products. Responsibilities include data architecture, feature stores, governance, security, lineage, performance and cost optimization, and cross-functional technical leadership. The role partners with data scientists, program managers, executives, and engineering teams to deliver reliable enterprise data solutions.