Top Data & Analytics Jobs

Lead GTM analytics across performance measurement, channel economics, data governance, forecasting, planning, and executive reporting. Own metric definitions, data standards, analytical priorities, and business requirements while partnering with Marketing, Data Science, Finance, RevOps, and Engineering. Analyze funnel, attribution, CAC, payback, conversion, retention, pipeline, and territory performance, translating findings into investment recommendations and strategic decisions for senior leadership.

Leads custom quantitative and qualitative market research projects from questionnaire and screener development through data collection, validation, analysis, reporting, and presentation. Serves as primary client contact, manages vendors, timelines, costs, and project risks, mentors junior researchers, and translates findings into actionable strategic insights. The role is fully remote with occasional travel for in-person interviews.

Design, build, and scale reliable data infrastructure, including event ingestion, stream processing, data warehouses, ETL pipelines, analytics tools, and machine learning systems. Optimize performance, reliability, security, and data quality across AWS regions and data centers. Collaborate with analytics and data science teams, troubleshoot complex systems, influence architecture, conduct code reviews, and mentor data engineers while helping establish engineering best practices.

Performs strategic and business analysis supporting sales, marketing, lifecycle, and product teams. Builds dashboards, recurring reports, business cases, scenario models, and presentation-ready insights. Maintains data quality, identifies performance issues, and supports leadership decision-making. Uses generative AI tools to automate reporting, accelerate analysis, and uncover growth opportunities.

Lead North American supply chain analytics by evaluating performance against forecasts and operating plans. Apply optimization, simulation, statistical analysis, data mining, and AI-enabled tools to improve reporting, forecasting, and decision-making. Conduct root cause analysis, drive continuous improvement, and translate complex operational and financial data into recommendations for senior and C-suite leaders. Partner cross-functionally to automate analytics and strengthen supply chain planning and performance.

Design, build, and own scalable data infrastructure for proteomics research and machine learning. Responsibilities include developing production data platforms and pipelines, integrating instruments and LIMS, creating cloud infrastructure with infrastructure-as-code and CI/CD, ensuring data integrity and lineage, and transforming raw experimental data into reliable ML-ready datasets. The role partners closely with scientific teams, establishes engineering standards, sets technical direction, and mentors colleagues.

Analyzes supplier deal performance, revenue opportunities, forecasts, and commercial risks for global travel partnerships. Supports supplier negotiations, models deal structures, develops strategic reporting and optimization plans, and translates complex data into actionable recommendations for leadership, Sales, Pricing, and Client Management. The role requires strong analytical, commercial, communication, stakeholder engagement, and strategic thinking skills.

Leads ticket and subscription revenue management, pricing, forecasting, sales reporting, and audience analytics. Develops dynamic pricing, inventory, promotion, subscription, and revenue strategies; builds forecasts, dashboards, and reports; analyzes customer behavior and sales performance; and translates data into recommendations for marketing, programming, finance, and sales. Manages relationships with analytics and pricing partners while coordinating cross-functional program setup and improving analytical capabilities.

Design, build, and optimize scalable data pipelines, warehouses, lakes, and processing systems for analytics and business intelligence. Ensure data quality, security, reliability, and cost efficiency while collaborating with data scientists, analysts, and engineers. Maintain technical documentation, support Databricks solutions, and apply emerging data engineering technologies. The role requires strong programming, SQL, ETL, orchestration, data modeling, cloud, and big data expertise.

The Product Analytics Manager analyzes product, merchandising, and assortment performance across channels and markets. Responsibilities include developing lifecycle models, evaluating newness and assortment productivity, creating analytical frameworks and reporting tools, maintaining an ETL-enabled analytics sandbox, improving product data quality, and automating recurring analyses. The role partners with merchandising, planning, strategy, data engineering, business intelligence, and analytics teams to translate data into commercially relevant decisions.