Identify high-value opportunities from product, customer, and operational data Evaluate ambiguous ideas quickly and determine what is feasible, useful, and worth shipping Identify high-value opportunities from product, customer, and operational data Build practical 80/20 solutions that create leverage quickly, then refine them based on traction Own end-to-end execution across data exploration, modeling, experimentation, backend integration, and productization Partner with engineering, product, design, and leadership to turn rough ideas into shipped capabilities Use ML, analytics, heuristics, and automation pragmatically rather than forcing a model where one is not needed Define success metrics, instrument outcomes, and improve solutions based on real-world usage Help shape how GitKraken uses AI and data to improve developer workflows, team velocity, and product experience. Deep experience in machine learning, applied AI, or a similarly hands-on product data role at a Senior level A track record of shipping data or ML-powered capabilities into real products or operational workflows Comfort moving from messy problem statements to practical execution without a lot of structure Ability to work across the stack, not just in notebooks Strong product judgment and a bias toward simple solutions that deliver measurable value Experience deciding whether a problem is best solved with ML, rules, analytics, automation, or workflow design Ability to balance speed and rigor, including knowing when "good enough to learn" is the right answer Strong communication skills and the ability to explain tradeoffs clearly to technical and non-technical partners Ownership mindset: you don't wait for perfect specs, and you follow through from idea to impact.