Top Tech Jobs & Startup Jobs in Chicago, IL

Leads demand intake, prioritization, governance, portfolio planning, resource capacity alignment, and delivery oversight across the Data Governance and Data Management Office. Develops executive dashboards, monitors portfolio health and milestones, escalates risks and dependencies, facilitates governance forums, standardizes program-management practices, and drives continuous improvement. Partners with senior leaders and cross-functional teams to align data initiatives with business value, organizational capacity, and strategic priorities.

Leads enterprise data product strategy, roadmaps, prioritization, adoption, governance, and lifecycle management for reference data, master data, metadata, and standards. Defines reusable, AI-ready products containing business meaning, rules, metrics, lineage, and context. Partners with data enablement, technology, analytics, governance, and business teams to scale reliable products, establish standards and service expectations, measure value, resolve issues, and drive stakeholder adoption.

Coordinates technical onboarding and ongoing operations for data partners and vendors. Ensures data delivery, ingestion, metadata, catalogs, documentation, and inventories remain accurate and current. Tracks data quality, SLAs, delivery performance, operational metrics, and issue resolution across business, technical, engineering, analytics, and vendor teams. Maintains centralized issue trackers, escalates risks, translates technical problems into business impacts, and drives cross-functional follow-through in a matrixed environment.

Leads rapid design, development, and validation of agentic AI proof-of-concepts. Partners with stakeholders, product, architecture, and engineering teams to identify opportunities, build LLM-based prototypes, evaluate emerging technologies, document methodologies, and transition successful solutions into production roadmaps. The role also mentors AI engineers and supports enterprise AI innovation.

Leads the design, prototyping, and validation of AI agents and autonomous workflows. Evaluates foundation models, agent frameworks, orchestration technologies, and developer tools; creates reusable proofs of concept and reference implementations; and partners with engineering, product, platform, and architecture teams to productionize successful innovations. Establishes best practices for prompt engineering, reasoning, memory, evaluation, and observability while mentoring AI engineers and promoting experimentation.

Leads strategy, roadmap, prioritization, adoption, governance, and lifecycle management for customer-facing payer, HCP, omnichannel, and engagement data products. Partners with data enablement, technology, analytics, and business teams to create trusted, reusable, AI-ready products incorporating semantic definitions, metadata, lineage, standards, and measurable business value.

Executive Director responsible for vision, roadmap, prioritization, governance, funding, adoption, and value realization across an enterprise data product portfolio. Leads innovative data products and offerings teams, partners with business, analytics, technology, DEO, and vendors, and drives build-versus-buy decisions, reusability, stakeholder engagement, and measurable outcomes across customer, patient, commercial, and foundational data domains.

Leads enterprise strategy, development, and adoption of applied AI, data science, and commercial intelligence capabilities. Oversees multidisciplinary teams, AI-powered products, scalable data and AI platforms, governance, model lifecycle management, and responsible AI practices. Partners with commercial and technology leaders to prioritize use cases, drive measurable ROI, build talent, and accelerate business growth, customer engagement, operational efficiency, and data-driven decision-making across a regulated, life sciences environment.

Lead MarTech product management maturity, governance, and operations across a complex portfolio. Establish scalable frameworks, KPIs, and dashboards; drive prioritization, planning, budgeting, and cross-functional alignment; partner with IT, marketing, vendors, and executives; and lead change initiatives including AI-enabled capabilities to improve delivery and ROI.

The Director, Analytics Infrastructure & Pipeline Operations is responsible for creating automated data pipelines and centralized feature stores for data science, leveraging AI technologies to optimize workflows and ensure data quality.