Lead Data Scientist

Ecolab Digital is hiring a Lead Data Scientist to build and maintain AI and data products for the Institutional and Specialty segment. The role owns end-to-end AI product development, covering classical machine learning, LLM-based applications, and multi-agent workflows to produce measurable commercial outcomes. Role Focus The Lead Data Scientist will identify AI opportunities tied to Institutional and Specialty business challenges, drive experimentation and delivery of digital data science and AI product innovations, and partner with internal stakeholders to translate business strategy and voice of customer into technical plans, build decisions, and lifecycle directions. Key Responsibilities Identify and define opportunities aligned to Institutional and Specialty business challenges, navigating a range of problem types and solution approaches. Drive experimentation and delivery of digital data science and AI product innovations aligned with the digital product vision. Partner with internal business stakeholders to translate business strategy and VOC into technical opportunities, builds, and lifecycle decisions, communicating clearly across levels. Architect and build AI solutions end to end across classic ML, LLM-based applications, and multi-agent systems, owning technical design decisions from the data layer through inference, API exposure, and product integration. Own the production lifecycle of AI agents and models, including QA, monitoring, drift detection, prompt and version management, and retraining pipelines for reliable customer-facing outcomes. Define and track effectiveness metrics for AI features in partnership with product and commercial teams. Design evaluation frameworks with responsible AI practices, including champion/challenger pipelines, automated regression testing, guardrails, and audit logging. Minimum Qualifications Bachelor’s degree in Data Science, Economics, Math, Statistics, or a related field with an emphasis on analytics, or a master’s degree with 5 years of experience in progressive data roles. 8 years of experience. 5 years of strong Python and SQL. Expert in writing clean, modular, production-grade code, with version control, unit testing, and code review treated as standard practice. 1 year of shipping production LLM applications, including prompt engineering as a real discipline (structured prompts, output schemas, exclusion rules), RAG over vector indexes, and combining GenAI reasoning with deterministic logic for reliable and auditable outputs. Hands-on experience building and orchestrating multi-agent systems, including sequential handoffs, tool-calling, and scheduled or DAG-based workflows, with judgment on when to use probabilistic reasoning versus deterministic rules. Proven experience building and operating evaluation and quality frameworks for GenAI output, including measuring improvements from prompt or model changes, calibrating against subject-matter-expert ground truth, and reducing hallucinations in customer-facing products. Experience with being a people manager. Proven ability to balance business needs with technical rigor and communicate approach, assumptions, and tradeoffs to technical and non-technical audiences. Excellent communication and presentation skills, including translating technical work into business context with structured, concise findings for diverse stakeholders. Hands‑on experience with PySpark and DataFrame APIs on a large‑scale distributed platform (Databricks strongly preferred), including experience governing data pipelines that combine operational, regulatory, sensor/IoT, and third‑party sources into a coherent data model. Immigration sponsorship is not available for this position. Preferred Qualifications Deep familiarity with the Databricks GenAI stack, including Model Serving, Unity Catalog, Vector Search, MLflow (including prompt registry and champion/challenger evaluation), Lakebase/managed PostgreSQL, and Databricks Asset Bundles. Experience with MCP (Model Context Protocol) servers and tools, conversational AI assistants, and emerging agent‑to‑agent (A2A) orchestration patterns. Experience exposing AI capabilities as production services and APIs and integrating them into customer‑facing digital products with attention to latency, reliability, versioning, and authentication. Proficiency across Microsoft Azure services (App Service, Functions, Key Vault, ADO Pipelines) and PowerBI, with comfort using cloud APIs and CI/CD across multiple environments. Strong data science foundation applicable to GenAI work, including EDA, statistical reasoning, metrics and evaluation design, sampling, and error analysis. Working knowledge of DevOps, git, Snowflake, and distributed compute platforms. Experience in Retail/Quick Service Restaurants businesses. Well‑developed and proven leadership, strategic thinking, and business acumen. Sharing a public GitHub profile or project portfolio is encouraged. Location and Schedule Naperville, IL (hybrid). St. Paul, MN is also an option. Travel: up to 10% of the time. Compensation The base salary range for this position is $153,900.00 - $230,800.00 per year. The role is eligible for annual bonus pay based on performance, per plan terms. Compensation decisions consider factors such as experience, education, training, and geography, and the company complies with minimum wage and overtime laws. Tools and Technologies Python, SQL LLM, RAG, vector indexes Multi-agent systems, PySpark, DataFrame APIs Databricks (including Databricks GenAI stack), Model Serving Unity Catalog, Vector Search, MLflow, prompt registry Champion/challenger evaluation, Lakebase, managed PostgreSQL Databricks Asset Bundles, MCP (Model Context Protocol) A2A orchestration patterns Microsoft Azure, App Service, Functions, Key Vault, ADO Pipelines PowerBI, CI/CD, DevOps, git Snowflake, distributed compute platforms, DAG-based workflows Unity Catalog, Vector Search, Model Serving, MCP (Model Context Protocol) Additional Notices Potential customer requirements: for certain customer‑facing roles, applicants may need additional background screens and/or drug and alcohol testing for customer credentialing. ADA accommodation: Ecolab will provide reasonable accommodations with the application process upon request as required by law. #J-18808-Ljbffr Ecolab