Top Data & Analytics Jobs

Develop and test sophisticated investment models using scientific methods, machine learning, quantitative techniques, and large datasets. Conduct independent research, create investment ideas, collaborate with engineers, analyze real-world data, and communicate complex findings. Participate in research discussions, academic seminars, and industry conferences covering statistics, machine learning, and data science.

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.

Analyzes organizational data, performs statistical analysis, evaluates potential impacts of data changes, and contributes to systems design, development, and integration. Applies mathematical calculations to recommend solutions for technical problems and supports completion of technical tasks within the systems lifecycle.

Summer Analyst on Citi’s Markets Quantitative Analysis team, developing quantitative models and analytics for derivatives, algorithmic execution, trading strategies, and risk management. The role includes a structured training program, quantitative modeling desk placement, a summer project, data science competition, desk rotations, and presentations to senior leadership. Candidates should have strong mathematical, statistical, programming, artificial intelligence, and machine learning skills, plus an interest in financial markets.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, governance, adoption, and delivery. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to create scalable Power BI and Snowflake capabilities, including AI-assisted analytics. Manages and develops the BI team, prioritizes demand, measures business value, and guides technical design while supporting trusted decision-making across the organization.

Leads risk analytics projects and teams for property and casualty reinsurance. Oversees advanced statistical and machine learning model development, validation, deployment, and adoption in underwriting. Partners with data scientists, engineers, actuaries, underwriters, claims, legal, and external data providers. Generates analytical opportunities, supports pricing, communicates complex findings, and promotes innovation across the actuarial organization.

The Director, Data Insights serves as the primary data advisor to executives and external stakeholders. Responsibilities include translating analytics into board-ready narratives, influencing strategic decisions, aligning data roadmaps with business value, resolving cross-functional priorities, promoting data-driven culture, and conducting rapid analyses using agentic tools.

Leads a team of data scientists and BI engineers responsible for demand forecasting, customer routing analytics, budgeting projections, and core business KPIs. Designs scalable Snowflake datasets, metric definitions, and Tableau self-service analytics; partners with Product, Engineering, and Finance; establishes analytical strategy and roadmaps; applies statistical and causal reasoning; and guides responsible AI-assisted analytics practices.

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.

Full-time computer science faculty position specializing in data engineering or data analytics. Responsibilities include teaching, developing data-focused curricula and degree pathways, leading program assessment and growth, recruiting adjunct faculty, building industry partnerships, advising students, and contributing to university committees and campus life. Candidates should have relevant graduate education or professional experience, teaching and program leadership experience, and a commitment to Christ-centered higher education.

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.

Lead science data and knowledge management at Audubon, enhancing data accessibility and usage across various scientific programs while collaborating with IT and Conservation Teams.

Supports specialty property underwriting and analytics teams by analyzing third-party data, identifying portfolio trends, maintaining dashboards and reports, conducting research, and contributing to pricing, portfolio strategy, market expansion, and process improvement initiatives. The intern also prepares leadership materials and collaborates with underwriters, analysts, and property leaders.

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.

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.

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.

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.