Top Analytics Jobs

Own the end-to-end analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, surface insights, and drive recommendations through execution. Partner with product, growth, finance, and operations leaders to influence decisions and improve key business outcomes.

Lead fraud detection analytics focused on account takeovers, scams, organized fraud rings, and coordinated attacks. Analyze large-scale datasets using Python and SQL, evaluate vendor and internal detection tools, support anomaly detection, and help develop fraud models, dashboards, and reporting. Communicate actionable insights to technical and business stakeholders while improving fraud prevention strategies and operational effectiveness.

Manage analytics consulting projects for Life Sciences clients, delivering marketing, commercial, Real World Data, market mix modeling, and predictive modeling solutions. Responsibilities include developing analysis plans, analyzing healthcare datasets, leading client discussions, presenting recommendations, ensuring quality and timely delivery, and managing team engagement. The role requires strong client-facing consulting skills, knowledge of biopharma commercial analytics, patient analytics, payer and market access concepts, and clear written and verbal communication.

Supports client teams through advertising and marketing campaign analysis, dashboard construction, data visualization, and report building. The internship runs January 25 through April 30, 2027, requires 20–30 hours weekly, and is conducted in person at the company’s Nashville office.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface actionable insights; influence leadership decisions; and drive initiatives through execution. The role requires first-principles problem solving, strong data skills, persuasive communication, and end-to-end ownership of ambiguous business problems.

Analyzes digital marketing, web, email, organic, voice, and chat performance; develops reporting, KPIs, measurement plans, tagging requirements, attribution analyses, and data-driven recommendations. Partners cross-functionally to evaluate initiatives, tests, customer segments, and subscription performance. Uses BI tools, SQL, analytical programming, and AI automation to generate insights and improve digital growth decisions.

Leads the Bank’s mortgage analytics and insights organization, overseeing managers and analysts who evaluate MPF and residential mortgage portfolios. Provides strategic analysis of portfolio performance, credit and market risks, mortgage trends, and regulatory developments. Advises senior leaders, regulators, rating agencies, and the Board; oversees reporting, regulatory submissions, advanced analytics, AI, automation, and process improvements. Responsible for organizational design, talent development, performance management, succession planning, and executive communication.

Leads an analytics team delivering actionable insights, forecasting, statistical analysis, reporting automation, visualization, and client-focused tools. Oversees analysts, develops team talent, enhances databases and analytical processes, manages client and vendor relationships, and presents recommendations to executives. The role requires advanced Excel, business intelligence, data mining, statistical modeling, cross-functional collaboration, and strategic leadership, with health insurance analytics experience preferred.

Lead enterprise data analytics and insights projects for Fidelity’s Legal, Risk, and Compliance organization. Define business questions, identify data sources, perform advanced analysis across structured and unstructured data, build automated workflows and business intelligence reports, and communicate actionable findings. Collaborate with Risk, Audit, Compliance, Legal, technology, customer-facing, and data-provider teams to develop scalable, data-driven solutions supporting risk management and decision-making.

Develops reporting, analytical tools, and data solutions that support strategic decisions, revenue growth, and operational efficiency. Partners with Customer, Marketing, and Digital teams to analyze customer behavior, identify trends, validate data, and translate complex findings into actionable recommendations for executives and business leaders. Leads cross-functional analytics initiatives, improves processes and methodologies, supports user adoption, and mentors junior analysts.

Analyze and maintain investment data, build quantitative models and performance attribution systems, automate reporting workflows, and create dashboards for investment teams. Partner with research, portfolio construction, risk, and technology stakeholders to translate business needs into reliable data solutions. Support data quality, model governance, backtesting, scenario analysis, factor research, process improvement, and evaluation of AI and machine learning capabilities.

Develop and maintain investment data solutions, quantitative models, performance attribution systems, dashboards, and reporting workflows. Partner with investment professionals to translate analytical needs into reliable data products supporting portfolio construction, manager selection, risk analysis, and research. Automate processes, improve data quality, apply model governance, and collaborate with technology and risk teams across global offices.

Analyze mobile application data using Adobe Mobile Analytics, including iOS, Android, and hybrid app analytics. Utilize Sitecatalyst and Omniture for insights.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

Lead quantitative research and analytics for political and commercial clients: design experiments and surveys, manage RCTs and statistical modeling, generate strategic insights, oversee a team of data scientists and analysts, and deliver client-facing recommendations.

The Quantitative Research Analyst develops client analytics models, collaborates with technology teams, conducts portfolio studies, and mentors junior staff.

The Fraud Analytics SME analyzes fraud detection patterns, guides teams in detecting fraud schemes, validates analytical outputs, and supports operational reviews and discussions.

The Senior Group Director of Growth Analytics drives strategies for multi-platform growth, manages analytics teams, and develops measurement plans for clients.

Support the Provider Risk Analytics team by performing data analysis and projects to monitor cost and revenue trends, identify improvement opportunities, model impacts for provider organizations, attend provider meetings, and learn value-based care and risk modeling.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Design and maintain scalable data pipelines, analytical datasets, models, metrics, dashboards, and analytics products. Use SQL, Python, cloud platforms, visualization tools, automation, and AI capabilities to transform complex data into actionable insights for leadership assessment and talent decisions. Partner with stakeholders, communicate findings, and manage governance, testing, documentation, deployment, and ongoing support.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Partner with marketing, product, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests, define acquisition and partnership levers, leverage machine learning for insights, and automate operational processes to improve efficiency and scalability.