Top Data & Analytics Jobs

Develop and execute data strategies to enhance fundraising efforts, lead analytics for donor engagement, ensure data quality, and manage a high-performing team.

Lead enterprise data, analytics, MDM, and integration strategy. Modernize cloud-native data platforms, manage data warehouse and API-first integration platforms, build/lead data engineering teams, enforce governance and data quality, enable analytics/AI/ML, and manage vendor relationships and managed services.

Perform operational and management audits, evaluate internal controls and compliance, analyze large datasets to assess policies and performance, identify risks and inefficiencies, audit vendor/contract compliance, verify statistical data, and draft and present audit findings with recommendations.

The Director leads Business Intelligence efforts, advancing data solutions, managing teams, and ensuring reliable analytics for decision-making across the University.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

The Market Intelligence Manager will drive strategic analysis, support CEO initiatives, and deliver business insights by analyzing market data and trends.

The professor will develop and teach courses in computer and data science, advance a research agenda, and engage in departmental collaboration and meetings.

Lead design and implementation of an automated fraud rule inventory and testing platform. Use data science and analytics to evaluate rule efficacy versus client friction, perform gap analyses, build synthetic test datasets, manage platform product requirements and QA, and deliver metrics and governance to senior management while supporting new product launches in crypto, digital assets, and banking.

The VP of Data Science & Strategy will transform complex business challenges into actionable growth strategies, leveraging data to influence decisions and drive company strategy.

Lead data science and analytics initiatives for healthcare, overseeing model development, data integrity, and large-scale automated analyses. Provide actionable insights, mentor teams, collaborate with cross-functional partners, evaluate payment integrity campaigns, and present findings to stakeholders to optimize revenue, quality, consumer experience, and healthcare costs.

The Global Head of Claims Data & Analytics will lead the data and analytics strategy, enhancing decision-making and improving claims management through advanced analytics and data governance.

The role involves teaching various data analytics courses, engaging in scholarly research, and providing service to the university and community, all while integrating Christian principles.

Lead the development of Transaction Monitoring models, leveraging advanced analytics to enhance detection of suspicious activities while managing a global team.

The job description provides a general overview of CVS Health’s mission, benefits, full-time schedule, compensation, and application timeline. Specific responsibilities, qualifications, education requirements, and technologies are not provided because the corresponding sections contain placeholder text.

Work with large datasets to ensure data quality, automate analytics workflows, and produce reliable, consumable insights. Investigate data behavior, communicate findings to technical and non-technical stakeholders, partner with engineering and product teams, and implement automation and AI-assisted tooling to improve accuracy and efficiency.

As a Junior Business Scientist, you will support analytics projects in data science and marketing effectiveness, focusing on data preparation, statistical modeling, dashboard development, and client interactions.

As a Business Scientist, you will engage with clients to deliver analytics solutions, apply statistical methods, and translate insights into actionable strategies while managing projects and collaborating with teams.

Lead a team of data scientists to optimize Databricks infrastructure using data science for capacity planning, reliability, and performance improvements.

Provide digital analytics and experimentation insights for Life Company digital teams. Use SQL, Python, and platforms like Adobe Analytics, Glassbox, and Optimizely to analyze customer journeys and funnels, run EDA, create visualizations, document methodology, and deliver actionable recommendations to influence product and business decisions.

The Lead, Data Science Internal Audit will implement statistical models, develop data frameworks for audits, mentor junior members, and present findings to stakeholders, enhancing audit practices through analytics.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Build and maintain scalable data pipelines for healthcare claims; implement de-identification and PII-reduction; ensure data quality and observability; integrate data stores and APIs; draft technical designs and documentation; gather product feedback and iterate quickly.

Lead paid media analytics for Life Company, using SQL/Python and advanced statistics to measure and optimize paid social/search and AI-powered search. Build audience segmentation, run incrementality/experimentation, create visualizations and recommendations, and partner with marketing to drive acquisition and engagement.

The role involves driving product strategy for data infrastructure, leading cross-functional teams, and implementing MLOps practices for data engineering solutions.

Lead a quantitative modeling team to develop and govern credit underwriting, pricing, collections, and portfolio risk models. Collaborate with stakeholders on acquisition pricing, marketing optimization, M&A risk assessment, and model validation. Oversee model performance, governance, and implementation to support lending strategies and maximize profitability while minimizing credit losses.