Top Data & Analytics Jobs

Design and implement scalable Snowflake-based data architectures on cloud (Azure/AWS). Build and optimize ETL using SnowSQL and Spark, tune performance, migrate data systems, document designs, collaborate with stakeholders, and mentor engineers while incorporating agentic AI into the data engineering SDLC.

Lead implementation of metadata governance and lineage for structured and unstructured data in cloud environments. Ensure metadata synchronization across catalogs, ESRI/Kubernetes, and enterprise repositories. Apply OpenLineage/Apache Atlas or similar tools, enforce DoD/NSG geospatial metadata policies, and advise clients on metadata strategy and integration.

Design, build, and deliver Power BI dashboards and analytics solutions using AWS, SQL, and Python. Develop data models, ETL pipelines, and analytics logic; incorporate AI/ML where appropriate. Partner with stakeholders, IT, and vendors to gather requirements, test solutions, and translate insights into business decisions to improve customer experience for a utility program.

Lead global pricing strategy and modernization for wholesale and specialty insurance, driving analytics, AI/ML integration, pricing model governance, catastrophe and transaction-level pricing support, and talent development to improve underwriting performance and return on capital.

Conduct execution-quality research across global markets: model market impact and slippage, design A/B tests and causal analyses, build optimization and simulation tools, and deliver analytics and decision support to traders and PMs for improved order routing and execution.

Implement, install and administer an advanced analytics platform and workspaces (SAS, Tableau, R, ML). Ensure IT policy compliance and service levels, support connectivity to data sources (Hadoop, Oracle, SQL Server), perform capacity planning, performance tuning, document procedures, troubleshoot issues, coordinate implementation with architects and service providers, and automate platform administration with scripting.

The role involves leading data science initiatives, managing large datasets, developing predictive models, and building a high-performing analytics team.

Lead development of advanced analytical and machine learning models to optimize forecasting, inventory placement, and supply chain flows. Automate reports, analyze large datasets, deliver insights to leaders, drive cross-functional initiatives, mentor junior analysts, and recommend process improvements to boost operational performance.

Lead and architect the Microsoft Fabric platform; manage a BI and data engineering team; deliver Power BI reporting, data integration, lakehouse/warehouse solutions; build pipelines, Python transformations, and ML models; enforce governance, CI/CD, and capacity management while partnering with stakeholders and data governance.

The Quantitative Researcher will focus on creating predictive alpha signals, applying ML techniques, and optimizing execution in cash equities. Close collaboration with teams to maximize P&L opportunities is key.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The Manager, Data Governance will lead the implementation of data governance strategies to support AI and analytics, ensuring data quality, compliance, and ownership while promoting data literacy across the organization.

The Clinical Statistician will provide statistical expertise and analysis in clinical research, focusing on high-dimensional data and methodologies, collaborating with medical groups for reports and FDA submissions.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

Build and maintain reports and dashboards, analyze large operational datasets (flight activity, utilization, ground/FBO), apply statistical and ML methods including LLM-assisted analysis, automate workflows, lead analytics projects, and translate recurring operational questions into repeatable tools to drive decisions.

Lead digital marketing measurement and data science, analyze digital data, develop statistical models, and collaborate with marketing teams for optimization and insights.

The Data Analyst will conduct full lifecycle analysis, develop reporting capabilities, monitor performance, and identify improvements in data quality and efficiency.

Design, implement, and maintain scalable data pipelines and platforms for structured and unstructured data to support AI/ML workloads. Ensure data governance, security, monitoring, and CI/CD for ETL workflows across on‑prem, cloud, or hybrid environments while collaborating with cross‑functional technical teams.

As a Data & Analytics Analyst, you'll collaborate with clients to create tailored solutions, implement prototypes, and share ideas to solve analytical challenges.

Lead and scale the enterprise data platform and analytics capabilities, defining strategy and roadmap. Hire and mentor global data engineering and analytics teams, deliver reusable data products, provide hands-on technical leadership, ensure AI-ready, governed data for analytics and ML/Generative AI, and partner with senior stakeholders to prioritize investments.

Hands-on principal data engineer defining enterprise-scale data architecture, building and optimizing data pipelines/integrations for analytics and ML, deploying production code, mentoring engineers, and partnering with product and ML teams to transform and analyze data for actionable insights.

Lead fraud analytics efforts to detect identity theft, fabricated entities, and emerging schemes. Validate models and rules via return- or case-level review, identify patterns, support stakeholder briefings, translate analytics into operational mitigation and treatment recommendations, and produce dashboards and documentation for leadership and oversight.

Design, build, and maintain scalable data pipelines and production-grade data products in Palantir Foundry. Implement ETL processes, ensure data quality, optimize pipelines, and collaborate with cross-functional teams. Serve as an independent performer and subject-matter expert, working with unstructured data and open-source/cloud tools for analytics and visualization.

The Global Head of Claims Data & Analytics will lead the data and analytics strategy, enhancing decision-making and improving claims management through advanced analytics and data governance.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.