Top Senior Analytics Jobs

The Senior Data Scientist will lead revenue-driving initiatives, optimize strategies, enhance data analysis techniques, and improve data pipelines for maximum revenue impact.

Perform financial due diligence data analytics for middle-market M&A: obtain, validate, normalize, analyze transaction data (revenue, costs, inventory), produce dashboards and visualizations, identify trends/outliers, and communicate insights to deal teams and clients.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Lead Compliance Data Analytics to research and analyze risk patterns (fraud, account takeover, payment fraud), deploy and iterate rules/models, partner with stakeholders to balance user experience and risk mitigation, drive business-centric analytics and strategic metrics, and build and manage a high-performing compliance analytics team.

Develop and execute quantitative models and analytical methods to assess credit risk for Single Family mortgage products (modification, short sale, foreclosure, distressed valuation). Independently design, implement, and validate predictive models, support business and risk decisions, perform data cleaning and processing, and collaborate with stakeholders to provide practical, innovative solutions.

Lead and support mixed-methods health services research projects, focusing on qualitative research design, data collection (interviews, focus groups), analysis, and reporting; assist with survey design, survey administration, data checks, IRB applications, literature reviews, and dissemination of findings.

Lead implementation and optimization of a fraud orchestration platform; perform advanced fraud analytics, develop detection models, rules and scenarios; support investigations and vendor onboarding; translate analytic insights into executive recommendations; collaborate with Fraud, Product, Technology, and Business stakeholders to reduce fraud losses and drive enterprise-wide controls.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead a team of data analysts to analyze complex datasets, build models and forecasts, ensure data quality, and present insights to influence business strategy and drive growth across cross-functional stakeholders.

The Senior Analytics Specialist develops processes for digital optimization and collaborates on A/B and multivariate testing through data insights.

Lead fraud detection analytics for payment card transactions: analyze large datasets with Python and SQL, implement real-time detection strategies, support anomaly detection for coordinated fraud, refine rules and models, and communicate insights to influence stakeholders and reduce risk.

The Associate Director will manage a team, develop statistical models for marketing analytics, and cultivate client relationships to drive business results.

The Manager will enhance health plan operations using data analysis, reporting tools, and stakeholder management to provide actionable insights and improve health outcomes.

The Senior Director leads a team in analytical characterization of biologics, overseeing strategies and advancing digital efforts in a fast-paced environment.

Conduct enterprise-wide data analysis, manage large data sets, develop insights and dashboards, and prepare reports for stakeholders in support of decision-making.

Lead end-to-end strategic projects to optimize health plan programs, perform data-driven analyses, build impact models, present executive recommendations, advise cross-functional stakeholders, mentor junior analysts, and monitor initiative outcomes to improve efficiency and care quality.

Perform advanced data mining and predictive modeling using SQL, Python, R, SAS and Power BI. Prepare recurring and ad-hoc portfolio performance reports, identify risk trends and KPIs, validate models, troubleshoot data issues, and present actionable analysis to management. Collaborate with IT and business teams to maintain large datasets and databases.

Lead development of climate- and catastrophe-focused analytics linking climate science, geospatial data, and demographic modeling to P&C business impacts. Design and validate models, integrate disparate datasets, produce visualizations and executive-ready recommendations, and operationalize climate-risk insights across cross-functional teams.

Write complex SQL queries and manipulate large datasets to produce end-to-end financial analysis of domestic and global roaming traffic. Gather requirements, identify data sources, rationalize results, produce written analysis, troubleshoot queries, and collaborate cross-functionally to make recommendations and support reporting needs.

This role involves leading AI-driven analytics for HR, designing data models, collaborating with stakeholders, and mentoring junior analysts to ensure data integrity and impact decisions based on insights.

Lead advanced analytics and experimentation to improve digital customer experiences. Translate business questions into testable hypotheses, analyze structured and unstructured data (including transcripts and platform logs), build data models and visualizations, deliver insights to senior leaders, and drive measurement strategy and dashboard automation using SQL, Python, Snowflake, Tableau, Adobe Analytics and related tools in an Agile environment.

As the Senior Fraud Strategy and Analytics Manager, you will analyze fraud trends, build predictive fraud models, implement prevention rules, and enhance risk profiles while collaborating with cross-functional teams in the financial services sector.

Lead and execute data analysis for ecommerce and subscription metrics, build dashboards and reports, generate actionable insights for marketing/product/ops, run A/B tests and cohort analyses, and mentor junior analysts while presenting findings to stakeholders.

Analyze large datasets and build/validate predictive models to identify and monitor portfolio risk. Produce recurring and ad-hoc reporting and management presentations, troubleshoot data issues, collaborate with IT and business partners, and support decision-making through actionable analytics.

The role involves coordinating meetings, managing action items, conducting advanced data analytics, and briefing senior leadership with insights from complex datasets.