Top Senior Data & Analytics Jobs

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Lead design and delivery of Snowflake-based data solutions, data models, ETL pipelines and data warehouse applications. Provide architecture direction, drive technology transformation and POCs, evangelize modern data architecture, collaborate with global stakeholders and Agile teams, and apply advanced analytics (ML/AI/GenAI) while ensuring data security and PII management.

Design, build, and maintain Databricks-based data platform and ETL/ELT pipelines. Collaborate with stakeholders, implement data quality checks and testing, monitor pipeline performance, document architecture, and coordinate cross-functional teams.

Leads cross-functional data management and analytics projects for pharmaceutical and life sciences clients. Responsibilities include data warehouse development, ETL and schema design, data analysis, process optimization, client communication, project management, business development, and mentoring junior staff. The role also provides strategic guidance, develops reporting solutions, manages timelines and resources, and contributes to internal data platform initiatives.

Administer, optimize, and secure enterprise Microsoft SQL Server environments. Lead performance tuning, high availability, disaster recovery, monitoring, automation, upgrades, patching, and migrations. Support reporting and analytics workloads using SSRS and Qlik, maintain documentation and operational processes, collaborate with application and infrastructure teams, mentor junior engineers, and participate in on-call support.

Analyze credit, fraud, pricing, and portfolio performance using internal and external data. Cleanse and validate data, monitor predictive models and risk strategies, develop statistical models, identify trends and data-quality issues, and communicate actionable insights to leadership. Collaborate cross-functionally with product, engineering, compliance, and enterprise risk teams to support strategic decisions, improve profitability, and manage B2B credit risk.

Own healthcare analytics data methodology, including episode grouping, provider attribution, cost standardization, quality measures, reference data, pipelines, QA, and production delivery. Translate feature requests into specifications and validated analytics. Reconcile results, establish recurring data-quality coverage, investigate failures, and collaborate with engineering, data science, product, clinical informatics, and customer teams. Advanced SQL and healthcare claims expertise are central to ensuring accurate, defensible customer metrics.

Own analytics for Customer Success and Operations by translating ambiguous business questions into metrics, reports, dashboards, and PRDs. Partner with senior leaders, CSMs, Analytics Engineers, and Operations teams to improve retention, permit turnaround, and organizational scalability. Build self-service dashboards, develop dbt models, document analytics assets, prioritize high-impact requests, and use LLM tools to accelerate SQL, reporting, and data-model development.

Build and maintain Snowflake and dbt data platforms, including ELT pipelines, tested models, orchestration, monitoring, documentation, access controls, and governance. Optimize performance and costs while ensuring reliable, discoverable data for internal dashboards, client products, and AI/ML use cases. Translate ambiguous stakeholder needs into durable solutions and apply strong software engineering practices, including Git, CI/CD, code review, Python, testing, and alerting.

Lead complex quantitative and qualitative consumer research projects for SEGA’s game portfolio from study design through analysis, synthesis, reporting, and stakeholder readouts. Partner with Product, Brand, Corporate Planning, and Publishing teams to translate business questions into actionable insights. Manage research roadmaps and budgets, ensure methodological quality, align stakeholders, and mentor junior researchers. Research areas include market sizing, segmentation, concept testing, playtests, pricing, messaging, brand health, and product tracking.