AI Applied Scientist II

Deliver impactful solutions by executing high‑leverage data science and analytics initiatives within a product area or feature team, ensuring measurable improvements to user and business outcomes. Lead the design and implementation of advanced model fine‑tuning pipelines, including Reinforcement Learning from Human Feedback (RLHF), to align AI system behavior with user intent and improve performance in real‑world scenarios. Own complex, end‑to‑end projects that combine technical depth with cross‑functional collaboration, influencing feature direction and prioritization rather than broad organizational investment decisions. Develop and maintain robust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise‑scale environments. Leverage AI to streamline workflows and enhance team productivity through intelligent automation and innovation. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND relevant internship experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field 1+ year(s) of generative AI experience. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.