Top Tech Jobs & Startup Jobs

Design data-heavy tools and services that translate ML, LLM, and complex data pipeline outputs into clear insights for researchers and evidence teams. Responsibilities include user research, prototyping, testing with real data, systems thinking, design system contribution, cross-functional workshops, workflow improvement, and balancing usability, technical constraints, business priorities, and regulatory requirements.

Supports Flatiron’s oncology product development as a clinical genomics subject matter expert. Interprets genomic test results, translates oncology workflows into product requirements, validates clinical decision-support features, and advises Product, Engineering, and Clinical teams. Develops educational materials on precision medicine and genomic testing, represents provider needs, and stays current on molecular diagnostics, targeted therapies, and oncology guidelines.

Designs, builds, and maintains data engineering solutions and ETL/ELT pipelines supporting oncology research and life sciences customers. Collaborates with clinical analysts, scientists, oncologists, and project managers to deliver reliable, high-quality data products. Responsibilities include translating research needs into technical solutions, mentoring engineers, participating in code reviews, improving processes, monitoring CI/CD, and troubleshooting pipeline issues.

Designs, builds, and maintains data solutions and pipelines supporting oncology research and life sciences customers. Collaborates with clinical analysts, scientists, oncologists, and project managers to translate research needs into reliable technical solutions. Ensures data quality, monitors CI/CD pipelines, resolves issues, improves engineering processes, participates in code reviews, and mentors junior engineers.

Lead the technical design and delivery of electronic prescribing modernization for OncoEMR. Build and review full-stack software using C#, VB.NET, React, and .NET services; modernize legacy WebForms workflows; develop safety-critical prescribing features; partner with product, QA, design, clinical, and vendor teams; manage complex projects from planning through rollout; and mentor engineers through code reviews, pairing, and design guidance.

Designs and builds instructional content for a remote clinical data abstraction workforce and internal Data Capabilities teams. Identifies learning and performance gaps, develops targeted training interventions, supports asynchronous and workflow-based learning, manages knowledge and process documentation, and improves training workflows using data-driven learning science and emerging technologies. Collaborates with clinical and operational teams to improve abstraction quality, efficiency, and workforce performance.

Lead product strategy, roadmaps, investment allocation, and development across three teams delivering clinical oncology workflow products. Manage and coach Product Managers while partnering with engineers, designers, clinicians, data scientists, customers, and vendors. Translate clinical, technical, and business needs into product requirements, integrate AI into workflows, establish KPIs, and drive safe, efficient, data-driven solutions from concept through launch and iteration.

Provide global hands-on and remote IT support across hardware, software, operating systems, mobile devices, identity systems, networks, endpoints, conference rooms, and workplace technology. Manage IT asset lifecycles, provisioning, access administration, endpoint configuration, patching, ticket resolution, and documentation. Support macOS, Windows, and iOS environments while delivering high-touch employee service and escalating complex issues to engineering teams.

Leads global developer platform and AI infrastructure capabilities supporting approximately 300 software and data engineers. Responsibilities include platform strategy, high-availability infrastructure, internal IT operations, AI tooling and governance, cost and security controls, enterprise AI adoption, and development of high-performing engineering leadership teams.

Lead product strategy and lifecycle for oncology clinical workflow applications. Partner with engineering, design, and clinical stakeholders to build data-driven and AI/ML-enabled solutions, ensure regulatory and safety compliance, define KPIs, and drive product discovery, launch, and iteration to improve clinical efficiency and patient outcomes.