Top Data & Analytics Jobs

Role involves executing trading strategies, developing quantitative models, and optimizing trading systems within a collaborative team environment.

Design and develop simulation frameworks for backtesting trading strategies, while collaborating with quantitative researchers on new trading ideas.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

Lead administration and optimization of the Snowflake data warehouse. Design and enforce data management and security policies, tune performance and costs, lead migrations and ETL initiatives, manage Snowflake roles/SSO, mentor DBAs, and maintain architecture documentation while collaborating with data engineers and analysts.

The role involves developing Power BI reports, building analysis models, transforming data, and applying security in reports. Strong communication and analytical skills are essential.

The internship offers military service members civilian work experience in data science through data analysis and related skillsets over 90-180 days.

The role involves designing and scaling data infrastructures for private equity, developing ETL/ELT pipelines, ensuring data quality, and collaborating with various teams on data governance.

The Data Governance Lead will implement data governance policies, ensure data quality, promote stewardship practices, and manage data governance councils.

The Jr. Database Developer & Business Analyst will design database solutions, maintain data integrity, and translate business needs into analytics, while collaborating with teams on reporting and process improvements.

Build the companys compute intelligence platform: stand up a data warehouse, ingest compute telemetry, billing, partner and CRM data, model it (dbt), build pipelines (Python/SQL), dashboards, and an AI-accessible query layer. Enable cross-functional teams to track supply, demand, utilization, capacity planning, and bottlenecks while ensuring reliable, documented, production-grade data infrastructure.