Top Data & Analytics Jobs

Lead and mentor a team of Data Analysts to own regional data strategy and quality across web and mobile products. Partner with product, engineering, and commercial teams to deliver insights, improve tools, automate workflows, and drive product and user growth.

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

Design and implement low-latency market making or liquidity-taking strategies. Build mathematical and stochastic models, analyze algorithmic convergence and boundedness, translate models into high-performance code, and collaborate with developers to deploy latency-sensitive alpha signals across multiple asset classes.

The ETL Lead will oversee ETL processes primarily using Informatica, manage Unix scripting, and possess extensive IT experience.

The Lead Data Architect will define enterprise data strategies, architect modern data platforms, lead pre-sales engagements, and ensure delivery excellence while mentoring team members.

The role involves transforming data into insights, conducting analysis, building data models, and collaborating with marketing teams to optimize campaigns. Strong skills in SQL, Python, and data visualizations are essential.

Lead technical onboarding and integration of clinical and claims data, manage EMR/API/SFTP integrations, design data flows and documentation, perform data QA/validation, troubleshoot issues, and manage go-live and post-implementation support.

The Performance/Data Analyst III leads advanced analytics, machine learning modeling, ETL development, and reporting for DOJ operational and strategic needs.

Design and deploy object detection and tracking modules; develop ML algorithms; guide team members; improve data governance and quality assessment.

The Information Architect leads the design and governance of enterprise data architecture, collaborates with stakeholders, and resolves complex data issues to ensure data integrity across investment processes.