Top Tech Jobs & Startup Jobs

Provides practical legal guidance on commercial, product, regulatory, privacy, and corporate matters. Drafts and negotiates NDAs, SaaS agreements, MSAs, SOWs, DPAs, and other contracts; advises on compliance, data security, incident response, AI, analytics, governance, disputes, audits, and investigations. Partners with Sales, Product, Engineering, Finance, and other teams while reporting to the SVP of Legal.

Leads complex, cross-functional programs across Scrum-based engineering teams. Facilitates Scrum events, coordinates integrated planning, manages dependencies, risks, capacity, milestones, and stakeholder alignment, and provides leadership visibility into program health. Coaches teams on agile practices, uses delivery metrics to improve predictability, and drives resolution of cross-team issues and trade-offs across iterative and deadline-driven initiatives.

Own the multi-quarter roadmap and strategy for Channel Data products. Analyze complex, high-volume data, lead customer discovery, prioritize initiatives, define requirements using AI tools, manage risks and dependencies, oversee release readiness, and communicate product decisions to senior leaders. Partner closely with engineering, data science, managed services, customers, and delivery teams to drive product outcomes and planning.

Designs, develops, and owns business intelligence dashboards, visualizations, analyses, and reporting solutions, primarily in TIBCO Spotfire and also Power BI. Responsibilities include data modeling, calculations, performance tuning, deployment workflows through GitHub, data quality collaboration, BI standards, risk identification, mentoring, and independent decision-making across a multi-tenant Life Sciences data platform.

Owns a portfolio of enterprise life sciences customers throughout implementation and steady-state operations. Responsibilities include resolving complex data issues, leading business reviews, analyzing performance, managing projects and change requests, improving processes, increasing product adoption, mitigating churn, and coordinating with technical teams. The role also develops customer documentation and training, delivers analytics and reporting enhancements, and coaches junior customer engagement team members.

Own the multi-quarter strategy and roadmap for Provider Rebate Management software. Lead customer discovery, process mapping, prioritization, business cases, requirements, and Agile delivery with Engineering and QA. Coordinate releases across customer-facing teams, identify AI and LLM automation opportunities, represent the product with customers, and mentor business analysts. The role requires deep understanding of US pharmaceutical market access, healthcare systems, provider rebates, and related commercial processes.

Analyze and certify conversational AI queries and answers against source data. Improve prompts, semantic layers, taxonomies, metadata, and labeling in collaboration with Product Management, Data Science, Engineering, and QA. Investigate data relationships and recurring accuracy issues, write technical requirements, document business logic, support testing and release communications, and provide data-quality input to the product roadmap.

Analyzes and certifies Prism’s AI-generated answers against source data, improves prompts and semantic layers, identifies recurring quality issues, and documents business logic. Partners with Product Management, Data Science, Engineering, QA, and business owners to define requirements, create accuracy test cases, improve data structures, influence the roadmap, and communicate product updates.

Analyzes and certifies conversational AI queries and answers against source data. Improves prompts, semantic layers, taxonomies, metadata, and data quality while partnering with Product, Data Science, Engineering, QA, and business owners. Documents business logic, writes technical requirements, develops accuracy test cases, contributes to roadmap prioritization, and communicates product updates.

Build and maintain Python-based automations, integrations, scheduled jobs, APIs, and data pipelines for operations teams. Improve processes before automating them, embed LLMs and AI agents into workflows, and connect internal systems, databases, and platforms. Measure time savings and error reduction, monitor production solutions, troubleshoot issues, document workflows, train users, and collaborate with DevOps and SRE on deployment and reliability.