Top Hybrid Senior Level Data & Analytics Jobs

The VP of Data will lead data strategy, manage data infrastructure, ensure data security, drive business insights, and integrate AI across the company.

Lead analytics for Patreon's feed ranking and recommendations, conducting experiments, building metrics, and collaborating with various teams to enhance content discovery and engagement.

This role involves designing and maintaining data pipelines, creating dashboards, and collaborating with stakeholders to drive analytics solutions for external data products.

The Data Engineer will design, implement, and optimize data pipelines for analytics and AI, transforming raw data into structured datasets, utilizing technologies like Databricks and SQL.

As a Senior Statistical Programmer, you will lead and support clinical trials by generating statistical programming deliverables, performing data analysis, and collaborating with cross-functional teams in a pharmaceutical setting.

The Staff Data Scientist analyzes customer funnel performance and designs frameworks to improve conversion rates and operational efficiency. Responsibilities include partnership with various teams, supporting experimental initiatives, and translating insights into actionable strategies.

Manage a team of analysts for PBM analytics, driving insights and scalable data products. Partner with business leaders for effective reporting and analysis.

The Sr Oracle Application Developer is responsible for designing and developing technical solutions using Oracle technologies, leading teams, and ensuring project deliverables. This role requires hands-on technical expertise in Oracle applications and systems analysis, guiding other developers, and liaising with external vendors.

The role involves identifying user friction points through data, maintaining KPIs, developing an analytical roadmap, and collaborating with cross-functional teams to enhance product experience. The manager will also mentor a team focused on technical excellence and accountability.

Lead data strategy and delivery for large-scale client transformations. Design modern data architectures, oversee analytics and ML initiatives, support sales as SME, grow client relationships, manage teams and resource strategies, and foster a collaborative culture focused on quality and business outcomes.