Senior Analytics Specialist

About the role:

We're looking for a Senior Analytics Specialist to head up ongoing analytics projects and help build analytical products people trust. You’re the analytical partner our product teams count on, from helping craft the analytics behind a solution’s value (strengthening internal product analytics and ROI storytelling) to refining the product vision and the details of a new analytical product for execution. Product brings the user, the problem, and the direction; you own what it takes to answer it well: defining the right metrics, shaping a coherent story and visualization design, and bringing the rigor that makes people trust the result.

From there, you translate that into the technical substance that gets built: context-rich metric definitions, dashboard requirements, and the validation that makes it hold up, so product leadership can stand behind the results rather than just present them. You’ll report into the Analytics Program Lead and assist in setting the analytics standards for the organization. If you like telling stories with data, leading small teams, and are passionate about rigorous, usable analytics, this is that role.

Key Responsibilities:

At Qventus, Analytics is treated as a first-class product, rather than a secondary output. As an Senior Analytics Specialist, you will:

• Partner with PMs to turn a product idea and initial story into a technically defensible analytics product, defining metrics precisely, shaping the dashboard narrative, and setting the validation methodology, and surfacing the gaps in the design before anything gets built
• Lead analytics projects as their technical owner: scoping key initiatives, running sprints, ticketing, leading project management for the pod, and holding the bar for what ships while keeping things unblocked.
• Build and steward the metric stories, definitions, and semantic context for your pod's scope, grounded in hands-on data exploration and documented so downstream users, future teams, and AI agents can trust them
• Own analytical quality for your pod, setting the bar for rigor and correctness, catching flawed definitions and misleading framings before they reach a customer, and holding ultimate technical responsibility for what the pod ships
• Bring analytical rigor into early product discovery, supporting the exploratory analysis and POCs that pressure-test ROI stories and surface what is really provable before the team commits to building

What We're Looking For:

• Sharp, experienced analytical thinking, with a track record of building out high-quality, narratively complete analytical components, not just running ad hoc analyses
• Versatile critical thinking, with demonstrated ability to ramp up quickly and translate general skills into tactical enablement, even without deep domain expertise
• Hands-on expertise with SQL and modern data warehouses (DBX preferred): deep enough to run analysis, support and debug metric definitions, and set the technical standard for your pod.
• Strong data visualization design & BI development skills (Sigma or similar)
• Demonstrated ability to partner with PMs as a trusted peer, turning rough ideas into defensible products and pushing on the thinking without friction
• Experience leading delivery for a small team: comfortable owning sprints, sequencing, and coordination, and getting good work out of a pod without becoming the bottleneck

It's a Plus if You Have…

• Experience leading dashboard development end to end, from design through validation and including hands-on build
• Expertise in the healthcare domain and familiarity with healthcare operational data, clinical workflows, hospital operations, or common healthcare measurement challenges
• Familiarity with data governance, metric governance, or semantic layer concepts, especially where consistency across teams, solutions, or customer implementations is critical
• Deeper technical expertise with hands-on data modeling and transformation experience and standards setting (dbt preferred)
• Experience contributing to analytics QA processes, validation workflows, peer review practices, or release readiness checks for customer-facing analytics