Analytics Product Engineer, Consultant
About The Position
Stellarus is hiring an Analytics Product Engineer to build user-facing analytics and AI experiences for healthcare products. The role develops React- and TypeScript-based dashboards, interactive data views, and embedded analytics agents that help users understand situations, investigate causes, and take appropriate actions. The engineer works within a cross-functional product team with Product, Design, AI/Data Science, and Data Services partners. The position owns the product experience rather than the backend data platform. It consumes governed APIs, data products, semantic metrics, and access controls provided by Data Services and turns them into intuitive, reliable analytics applications. The role also contributes reusable interface patterns, product instrumentation, and accessible, secure, explainable, performant experiences appropriate for a regulated healthcare environment. Stellarus is part of the Ascendiun Family of Companies. Its workplace model emphasizes purposeful in-person collaboration and flexibility; most teams come into the office two days per week. The company may require more office presence based on business needs. The role is based in a physical office and work-from-home office/deskwork environment, with a sedentary activity level for most of the workday.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, Business Analytics, Information Systems, Statistics, Mathematics, Engineering, or a related quantitative field.
- Minimum of seven years of relevant professional experience in software/application development.
- Demonstrated experience building production web applications with React and TypeScript.
- Experience building dashboards, data-dense interfaces, interactive visualizations, embedded analytics, or other decision-support products.
- Experience integrating front-end applications with REST or GraphQL APIs, authentication, authorization, and role-based experiences.
- Strong product judgment and ability to turn complex user workflows and data into clear, usable interfaces.
- Familiarity with modern front-end testing, observability, performance optimization, accessibility, and CI/CD.
- Analytics experience including data concepts, governed metrics, APIs, SQL, and Python.
- Ability to collaborate effectively across Product, Design, Data Services, AI/Data Science, and business teams.
Nice To Haves
- Experience integrating AI, LLM, or agent capabilities into customer- or employee-facing products.
- Experience designing conversational or agentic user experiences, including citations, evidence, feedback, quality evaluation, and guardrails.
- Experience with visualization libraries such as ECharts, Vega, Plotly, Recharts, or similar.
- Experience working in healthcare or another regulated environment.
Responsibilities
- Build polished, production-quality analytics applications using React and TypeScript.
- Create interactive dashboards, visualizations, KPI views, filters, drilldowns, tables, alerts, and exports that make complex information easy to use.
- Embed analytics agents into dashboard workflows to support natural-language questions, anomaly investigation, trend explanations, context-aware recommendations, and exploration of supporting evidence.
- Design agent experiences in the product, including suggested prompts, conversational interactions, insight cards, citations, confidence indicators, feedback mechanisms, and handoff paths.
- Partner with Product and users to understand decision workflows, validate ideas, and help shape a prioritized product backlog.
- Collaborate with Data Services to consume governed data APIs, approved metrics, and semantic data products.
- Collaborate with AI/Data Science teams to integrate agent capabilities, model outputs, retrieval, evaluations, streaming responses, and user feedback loops into the product.
- Create reusable front-end components and design patterns for analytics and agent experiences across products.
- Instrument the product to measure adoption, engagement, performance, error rates, agent usefulness, answer quality, and business outcomes.
- Ensure analytics and AI experiences are accessible, secure, explainable, performant, and appropriate for a regulated healthcare environment.
- Participate in discovery, design reviews, sprint planning, demos, and ongoing product improvement.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
