Senior Associate - AI Product Scientist, Decision Intelligence

Location Designation: Hybrid - 3 days per week Role Overview Join Enterprise Intelligence as an AI Product Scientist supporting Decision Intelligence products that help field professionals make better decisions through data‑driven insights and AI‑powered recommendations. This role combines applied machine learning, experimentation, product strategy, and generative AI to create intelligence products that drive measurable business outcomes. As an AI Product Scientist, you will own a product domain end‑to‑end, including model development, signal generation, experimentation frameworks, content personalization, and roadmap planning. Working closely with product leaders, engineers, designers, and business stakeholders, you will translate complex behavioral and transactional data into actionable intelligence while ensuring solutions are scalable, measurable, and aligned with user needs. This role is ideal for a senior individual contributor who thrives at the intersection of data science, product management, and business impact. What You’ll Do Design, develop, deploy, and monitor machine learning models, propensity scores, and behavioral signal frameworks that power decision intelligence products and influence business outcomes. Lead experimentation efforts, including hypothesis development, measurement strategy, holdout design, causal analysis, and performance reporting to evaluate the effectiveness of intelligence products. Develop and optimize generative AI solutions, including prompt strategies, personalization logic, content generation workflows, and testing methodologies that enhance user engagement and decision‑making. Partner with product leaders to define priorities, shape roadmaps, evaluate opportunities, and translate business objectives into scalable AI and analytics solutions. Contribute to shared machine learning platforms, reusable feature assets, and enterprise intelligence capabilities that accelerate innovation across multiple products and business domains. What You’ll Bring Required Skills Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field; advanced degree preferred. Experience developing, deploying, and supporting production machine learning models that directly influence business processes or customer outcomes. Strong proficiency in Python and SQL, including large‑scale data analysis, feature engineering, model development, and experimentation workflows. Experience designing and evaluating experiments, including A/B testing, holdout methodologies, causal inference techniques, and statistical measurement frameworks. Ability to communicate complex analytical concepts, model behavior, and business implications to both technical and non‑technical audiences. Demonstrated experience influencing product direction, prioritizing work, and partnering with cross‑functional stakeholders to deliver measurable outcomes. Preferred Skills Experience developing generative AI or LLM‑powered applications, including prompt engineering, content generation, personalization, and governance frameworks. Familiarity with Databricks, MLflow, dbt, cloud‑based data platforms, feature stores, and modern machine learning infrastructure. Experience with recommendation systems, propensity modeling, graph analytics, behavioral scoring, or decision intelligence applications. Background in financial services, insurance, distribution analytics, or other highly regulated industries. Pay Transparency Salary Range: $100,000 – $143,000 Overtime eligible: Exempt Discretionary bonus eligible: Yes Sales bonus eligible: No Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program. #J-18808-Ljbffr New York Life