Top Data & Analytics Jobs

Develop and deploy advanced statistical and ML models on large-scale alternative datasets to generate investable signals, partner with investment teams, evaluate data quality, and drive novel data-driven research with commercial impact.

Conducts research and analytical projects by acquiring, validating, and analyzing large datasets. Applies statistical methods, trend analysis, scenario modeling, and data visualization to produce actionable insights for district stakeholders. Partners with teams and leaders to define reporting needs, communicates findings, supports performance measurement, and facilitates data literacy training. Serves as the primary analyst for assigned focus areas.

Leads content analytics by designing reporting systems, analyzing performance across digital platforms, generating data-driven insights, advising content teams, automating data collection and analysis, and presenting findings to senior and non-analytical audiences. The role also uses experimentation, data science techniques, LLM prompting, and agentic AI tools to improve content performance.

Leads North American insights, analytics, and AI delivery for underwriting teams. Translates business priorities into data products and analytics solutions, drives measurable value and adoption, oversees AI-enabled transformation, partners with underwriting and enterprise Data & Analytics leadership, and develops high-performing teams. The role also promotes responsible AI governance, agile delivery, scalable solutions, and evidence-based decision-making across underwriting and portfolio management.

Supports data, analytics, systems, automation, and AI initiatives within clinical development. The intern contributes to clinical trial process analysis, data quality improvement, operational decision-making, technology-enabled solutions, and project documentation. The role involves evaluating AI tools, collaborating with cross-functional teams, learning new technologies, and generating actionable insights for pharmaceutical research and development.

Conduct quantitative research for a global, mid-frequency statistical arbitrage portfolio. Responsibilities include exploring alternative datasets, developing trading signals, improving portfolio construction, risk and transaction cost models, applying machine learning and data science techniques, writing production-quality code, and managing research projects from idea generation through implementation.

Provides analytical and lifecycle support for U.S. Navy electromagnetic warfare, decoy, and SEWIP systems. Applies operations research, data science, logistics analysis, reliability and maintainability engineering, mathematical modeling, simulation, optimization, and what-if analysis to improve system readiness, operational availability, resource allocation, and lifecycle performance. Develops performance metrics, evaluates alternatives, analyzes complex datasets, and delivers recommendations and decision-support products to technical and program leadership.

As a Decision Analytics Consultant, you'll leverage RWD and RWE analytics to support pharmaceutical clients by generating insights and conducting analyses for evidence generation and HEOR studies.

Analyze alternative data to uncover macroeconomic insights relevant to rates and foreign exchange markets. Develop expertise in market-driving themes and KPIs, produce written and visual research, communicate findings to investment professionals, and collaborate with data scientists, engineers, sourcing teams, and Compliance to create actionable investment research.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

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.

Leads Mattel’s global insights and analytics organization, integrating consumer, shopper, retail, cultural, market, and business intelligence. Shapes enterprise strategy, identifies growth opportunities and risks, establishes measurement frameworks, applies predictive analytics, AI, and data science, and translates complex information into actionable executive recommendations. Builds a globally integrated, high-performing team and evolves its capabilities, operating model, technology, and partnerships to improve decision quality and measurable business outcomes.

Provides advanced decision science and analytics support across life, health, and annuity insurance. Gathers, transforms, and analyzes disparate data using statistical and quantitative methods; develops insight-to-action recommendations, visualizations, and executive presentations; documents methodologies and validation; and partners with product, underwriting, sales, and leadership teams to influence strategy and business outcomes.

Teach undergraduate and graduate information systems and analytics courses, including course preparation, student assessment, grading, advising, and office hours. Participate in departmental, university, professional, and community service, contribute to student learning assessment, and maintain professional activity through scholarship, conferences, pedagogy, or industry practice.

This role involves delivering analytics for Finance & Strategy, developing data pipelines, and producing insights to inform leadership decisions.

Lead and mentor analytics engineers while building scalable data foundations, instrumentation, experimentation practices, AI-assisted analysis tools, ETL/ELT pipelines, and self-service datasets. Partner with data scientists, engineers, product managers, designers, and researchers to improve data quality, documentation, metric investigations, and insight-driven decision-making. Drive analytics engineering strategy, workflow optimization, and responsible use of AI across analysis and development processes.

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 leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

Lead the strategy and execution of real-world data capabilities, focusing on data lifecycle management, vendor relationships, and collaboration with various teams to deliver analysis-ready datasets.

Analyze business data, conduct exploratory and ad-hoc analyses, build reporting frameworks, and monitor data science models. Use SQL, Python, Snowflake, and dbt to clean and model data, investigate trends and anomalies, evaluate hypotheses, and communicate actionable insights through visualizations, reports, and presentations to technical and non-technical stakeholders.

The Senior Data Scientist will solve complex problems, mentor junior team members, conduct analyses, build models, and collaborate with various business units to enhance data science capabilities and strategies.

Lead a team of data scientists to enhance infrastructure through data science, focusing on capacity planning, performance optimization, and customer experience.

Leads specialty exposure management for non-natural catastrophe and liability portfolios across insurance lines. Oversees analysts performing pre- and post-bind modeling, portfolio production, reporting, regulatory submissions, data quality, and model validation. Partners with underwriting teams to optimize risk-adjusted capacity deployment, presents portfolio insights to senior stakeholders, manages outsourcing relationships, and advances exposure management tools, workflows, AI, automation, and analytics capabilities. Requires extensive insurance or reinsurance catastrophe modeling experience and strong leadership, risk governance, SQL, and analytical skills.

As a Sr Director of Consumer Analytics, you will lead insights into consumer behavior, manage a team, and influence senior leadership with data-driven strategies to enhance business performance.

Designs, develops, tests, maintains, and optimizes data pipelines and software systems using SQL, Python, and Apache Airflow. Supports technical projects, documents systems, troubleshoots application performance, evaluates user requirements, and develops technical specifications. Collaborates with epidemiologists, statisticians, and researchers, while mentoring staff and translating academic research needs into software solutions.