• Establish and maintain enterprise-level data management practices aligned with Level 4–5 CMMI target operating maturity; formal appraisal not required • Identify authoritative data sources, standardize data definitions, resolve duplicate or conflicting data elements, fill metadata gaps, and address reporting inconsistencies across OAA applications, SQL Server 2022 databases, SSRS reports, Power BI, SharePoint, and Power Apps • Develop and maintain data dictionaries, metadata documentation, stored procedure inventories, and report-to-data-source traceability • Assist with data-related inputs for ATO documentation and audits • Propose master data management recommendations as part of the Task 2 portfolio review; no specific MDM platform is required, but any proposed approach must align with the Microsoft-based OAA environment and comply with VA security and ATO requirements • Propose data fabric or metadata-driven approaches, subject to Government approval

Role Description We are looking for a Lead Data Scientist with strong expertise in Large Language Models (LLMs) and Python to design AI-powered chatbot solutions for specialized use cases. The ideal candidate brings a solid foundation in Natural Language Processing (NLP) and Conversational AI, along with hands-on experience in hallucination prevention, Responsible AI and compliance, and data analysis. - Team up with cross-functional groups spanning product, analytics, and engineering to build and refine a shopping assistant chatbot. - Craft and enhance prompt engineering strategies to elevate chatbot interactions. - Build LLM-based agents that connect with APIs, databases, and external tools through function calling. - Safeguard chatbot reliability and prevent hallucinations by applying model evaluation techniques. - Use A/B testing frameworks to measure and steadily improve chatbot performance. - Apply Responsible AI and compliance principles to secure ethical and regulatory alignment. - Perform exploratory data analysis to uncover insights and prepare structured requirements for the data engineering team. - Advise cloud engineering teams on the infrastructure needs behind AI-powered chatbot solutions. Qualifications - No less than 5 years of hands-on professional experience in data science. - At least 1 year of experience in people management or team leadership, covering a team of 5 or more FTEs. - Deep expertise in LLMs, including work with OpenAI APIs on Azure. - Strong Python capabilities for integrating and optimizing AI workflows. - Practical background in creating AI agents that use function calling to interact with external tools and databases. - Familiarity with hallucination prevention techniques for ensuring chatbot accuracy and reliability. - Solid grasp of Responsible AI and compliance best practices, including ethical AI guidelines. - Experience in Natural Language Processing (NLP) and Conversational AI development. - English at B2 level or higher, with strong written and spoken communication skills. Requirements - Applied experience with A/B testing and experimentation in close partnership with analytics teams. - Ability to shape and roll out a testing strategy that leverages key performance metrics for chatbots. - Proficiency in exploratory data analysis (EDA) to extract insights from data. - Skill in defining and communicating data requirements to the data engineering team. - Awareness of cloud services, either through hands-on experience or the capability to specify requirements for cloud engineering teams.

• Analyze, estimate & define data transformation req. to load data into EDW, Snowflake, Postgres, S3 (enterprise production & custom-built analytics environment). • Create ETL architecture & design flows to illustrate data mvmt from production to analytics environments (new & legacy AWS analytics environments). • Design & develop database code software. • Analyze project & make strategy for analytics data solutions & AI model support & deployment. • ETL & analytics S3 storage projects. • Lead analytics/data science ETL projects. • Lead team. • Evaluate organization's tech. needs, create POCs for new implementation or tech. enhancement & recommend improvements.

Role Description The Data Platform team at Whatnot builds services that improve our core product experience and unlock meaningful business value. In this role, you will: - Define technical direction and lead development of critical data platform systems that power next-generation capabilities at Whatnot. - Lead the buildout and evolution of our data orchestration and streaming platforms, helping drive them from early platform investment to production-ready usage across the company. - Design scalable, reliable, multi-tenant data infrastructure rather than simply building pipelines on top of an existing platform. - Own core platform concerns including scalability, performance, reliability, SLOs, and operational excellence for data processing systems. - Build high-quality systems that support real-time analytics, event-driven applications, and machine learning infrastructure needs across Whatnot. - Make key decisions about how data systems should be integrated across Whatnot, and then partner cross-functionally to bring that architecture to life. - Collaborate closely with engineering partners across product, platform, machine learning, and data to enable fast, safe, and scalable development. - Help shape broader company architecture across orchestration, stream processing, real-time systems, analytics, and content understanding. - Apply DevOps/SRE practices, including CI/CD, infrastructure automation, monitoring, and incident response, to keep platform systems reliable at scale. - Help define and enforce data governance and compliance standards across our data lake and downstream systems. Qualifications - 8+ years of experience in software engineering. - Ability to write well-tested, API-driven applications and services that run at scale in production. - Track record of building scalable, high-performance distributed systems. - Strong experience with streaming data systems (e.g., Kafka, Flink, or Pulsar) and/or orchestration platforms (e.g., Airflow, Dagster, or Temporal). - Hands-on experience designing and operating stateful, real-time data pipelines at scale, including concepts like checkpointing, state management, and watermarking. - Experience evaluating architectural tradeoffs in data processing and orchestration systems. - Experience building multi-tenant or end-to-end data infrastructure that supports multiple teams or production use cases. - Expertise in managing cloud data stores (Snowflake, BigQuery, Redshift, etc.) and data lake architectures (e.g., AWS S3). - Strong experience supporting operational systems to ensure uptime, reliability, and maintainability. - Familiarity with DevOps/SRE practices and CI/CD tooling, including GitHub and GitHub Actions. - Understanding of data governance and compliance principles. Requirements - Experience managing cloud technologies (AWS or Google Cloud) and comfort with infrastructure-as-code approaches (for example, Terraform). - Proficiency in at least one server-side programming language (preferably Python), common algorithms and data structures, and software design principles. - Self-starter ethic, with the ability to thrive under a high level of autonomy. - Exceptional interpersonal and communication skills. Benefits - Generous Holiday and Time off Policy. - Health Insurance options including Medical, Dental, Vision. - Work From Home Support. - Home office setup allowance. - Monthly allowance for cell phone and internet. - Care benefits. - Monthly allowance for wellness. - Annual allowance towards Childcare. - Lifetime benefit for family planning, such as adoption or fertility expenses. - Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally. - Monthly allowance to dogfood the app. - Parental Leave: 16 weeks of paid parental leave + one month gradual return to work. Company Description Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes.