The Data Scientist will support the development and optimization of a GenAI-powered sales enablement platform designed to help sales advisors interact with enterprise data through a conversational interface. This role focuses on preparing and analyzing complex datasets, generating insights, and supporting evaluation processes for LLM-driven features. The Data Scientist will collaborate with product, sales, and engineering teams to improve data pipelines, enhance analytics capabilities, and ensure reliable AI-driven insights that support sales workflows. The position requires strong analytical and programming skills, hands-on experience with Python, SQL, and modern data platforms, and familiarity with LLM integrations and machine learning techniques. KEY RESPONSIBILITIES Prepare, clean, and analyze datasets used for training, validating, and evaluating GenAI and LLM-based features Collaborate with product, sales, and business stakeholders to understand advisor workflows, data needs, and key performance metrics Build dashboards and reporting solutions to track adoption, performance, and business impact of sales enablement tools Support prompt evaluation, annotation, and quality assurance processes to improve AI-generated outputs Contribute to the development of structured knowledge bases, taxonomies, and metadata to support RAG-based systems Generate insights to improve sales processes and enhance advisor and end-user experiences Develop analytics-driven solutions that support business goals and operational improvements Analyze large and complex datasets and connect multiple internal data sources for unified insights Translate analytical findings into clear business recommendations for stakeholders Document data sources, methodologies, and processes to support continuous improvement Collaborate with subject matter experts to understand business processes and develop analytical approaches Assist with ongoing improvement of data pipelines and LLM integration with conversational interfaces Support optimization of data and LLM pipelines that power the internal Data Copilot platform Log tasks and project updates using collaboration tools such as Jira Provide guidance and feedback to junior analysts or data scientists when needed REQUIRED QUALIFICATIONS 3–5 years of experience as a Data Scientist, Data Analyst, or in a related analytical role Strong proficiency in Python for data analysis and machine learning workflows Strong SQL skills and experience working with relational databases Hands‑on experience with Git version control including branching and pull requests Experience with exploratory data analysis, feature engineering, and model evaluation techniques Proficiency with BI tools such as Power BI, Tableau, or similar visualization platforms Experience working with complex datasets across multiple systems Familiarity with LLM implementations, prompt engineering, and LLM guardrails Strong problem‑solving skills and the ability to translate complex technical findings into business insights Ability to work independently and manage loosely defined tasks in a fast‑paced environment Strong communication and collaboration skills for working with cross‑functional teams Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or equivalent technical experience PREFERRED QUALIFICATIONS Experience working with Databricks, Spark, or modern data engineering platforms Exposure to RAG pipelines or GenAI data architectures Experience with Azure cloud environments Familiarity with MLOps practices Background working with sales datasets or sales operations workflows Exposure to insurance industry data models or advisor‑based business environments #J-18808-Ljbffr