Data Scientist 

Job Description

Responsibilities

• Own scoring quality end to end: evaluator design, rubric anchoring, calibration, and accountability for accuracy against expert benchmarks
• Build and run the continuous evaluation harness: gold sets, bias diagnostics, drift detection, and the pre-release gate that every scoring change must clear
• Define and publish assessment quality KPIs (human to AI agreement, reliability, classification accuracy, bias indicators, latency, cost per assessment) on dashboards anyone in the company can reference
• Lead the analytics investigations behind assessment decisions: performance studies, impact simulations, root cause analysis when scores look wrong
• Ship measurement improvements end to end: implement and coordinate with tech, own the spec, the validation, and the quality bar in both cases
• Be Workera’s liaison between AI governance and InfoSec: stay current on frameworks like GDPR and the EU AI Act, and turn that into the evidence we show in audits, security reviews, and enterprise diligence when customers ask how we use AI in our assessments
• Empower partners across Product, Engineering, and GTM to get the data and analysis they need autonomously, by building AI tooling and documentation rather than answering each request yourself

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