Lead Data Scientist

Ecolab
Naperville, IL, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Compensation
$153,900.0 - $230,800.0
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Audit Trail Unit Testing Microsoft Azure Code Review DevOps Digital Data Github Python (Programming Language) PostgreSQL Machine Learning
+23 more
Software Product Management Regression Testing Power BI Search Technologies SQL Databases Management of Software Versions Retrieval-Augmented Generation Snowflake Multi-Agent Systems Generative AI Agentic-AI Git Data Layers Pyspark Low Latency Production Code Machine Learning Operations Model Context Protocol Software Version Control Data Pipelines Key Vault Databricks Agent2Agent Protocol

Job description

Ecolab Digital is seeking a commercial solution focused Lead Data Scientist to unlock the value in data assets while creating, maturing, and maintaining unique offerings for customers in the Institutional & Specialty segment.

In this role, you will sit at the intersection of AI engineering and data science. You’ll be partnering with digital product, marketing, sales, and engineering teams to design, build, and ship intelligent solutions that drive measurable commercial outcomes. You will own the end-to-end execution of AI product development across classical ML, LLM-based applications, and multi-agent/agentic workflows, translating business strategy into production-grade systems that scale., * Identify and define opportunities aligned to Institutional & Specialty business challenges, navigating a wide range of problems and solution approaches.

  • Drive experimentation and delivery of digital data science and AI product innovations aligned to the overall digital product vision.
  • Partner with a broad range of internal business stakeholders to translate business strategy and VOC into technical opportunities, builds, and lifecycle decisions, communicating clearly and consistently at every level.
  • Architect and build AI solutions end to end across classical ML, LLM-based applications, and multi-agent systems. You will own the technical design decisions from the data layer through inference, API exposure, and product integration.
  • Own the production lifecycle of AI agents and models. This covers QA, monitoring, drift detection, prompt and version management, and retraining pipelines, so we ship outcomes that are reliable and credible in customer-facing products.
  • Define and track effectiveness metrics for AI features in partnership with product and commercial teams.
  • Design evaluation frameworks with built-in responsible AI practices. This includes champion/challenger pipelines, automated regression testing, guardrails, and audit logging.

Requirements

  • Bachelors Degree in Data Science, Economics, Math, Statistics or related field with an emphasis on analytics or 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, and treating version control, unit testing, and code review as standard practice.
  • 1 year’s shipping production LLM applications: 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, auditable outputs.
  • Hands-on experience building and orchestrating multi-agent systems, including sequential handoffs, tool-calling, and scheduled or DAG-based workflows, with good judgment on when to use probabilistic reasoning versus deterministic rules.
  • Proven experience building and running evaluation and quality frameworks for GenAI output. You can measure whether a prompt or model change actually made things better, calibrate against subject-matter-expert ground truth, and keep hallucinations in check in customer-facing products.
  • Experience with being a people manager
  • Proven ability to balance practical business needs with technical rigor, and to clearly explain your approach, assumptions, and tradeoffs to both technical and non-technical audiences.
  • Excellent communication and presentation skills. You can translate technical work into business context and deliver structured, concise findings to a wide range of stakeholders.
  • Hands-on experience with PySpark and DataFrame APIs on a large-scale distributed platform (Databricks strongly preferred), and experience governing data pipelines that pull real-world sources (operational, regulatory, sensor/IoT, third-party) into one coherent data model.
  • Immigration sponsorship is not available for this position., * Deep familiarity with the Databricks GenAI stack: Model Serving, Unity Catalog, Vector Search, MLflow (incl. 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 auth.
  • Proficiency across the Microsoft Azure suite (App Service, Functions, Key Vault, ADO Pipelines) and PowerBI, and comfort with cloud APIs and CI/CD across multiple environments.
  • Solid data science foundation that carries into GenAI work: EDA, statistical reasoning, metrics and eval 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, & business acumen
  • Sharing a public GitHub profile or project portfolio is encouraged; we’d love to see examples of your hands-on work where available.

Benefits & conditions

Annual or Hourly Compensation Range The base salary range for this position is $153,900.00 - $230,800.00. This position is eligible for annual bonus pay based on performance, per plan terms. Many factors are taken into consideration when determining compensation, such as experience, education, training, geography, etc. We comply with all minimum wage and overtime laws.

About the company

If you are viewing this posting on a site other than our Ecolab Career website, view our benefits at jobs.ecolab.com/working-here.

Potential Customer Requirements Notice

To meet customer requirements and comply with local or state regulations, applicants for certain customer-facing roles may need to:

  • Undergo additional background screens and/or drug/alcohol testing for customer credentialing.

Americans with Disabilities Act (ADA)

Ecolab will provide reasonable accommodation (such as a qualified sign language interpreter or other personal assistance) with our application process upon request as required to comply with applicable laws. If you have a disability and require accommodation assistance in this application process, please visit the Recruiting Support link in the footer of each page of our career website.

Our Commitment to a Culture of Inclusion & Belonging

At Ecolab, we believe the best teams are inclusive. We are on a journey to create a workplace where every associate can grow and achieve their best. We are committed to fair and equal treatment of associates and applicants and recruit, hire, promote, transfer and provide opportunities for advancement based on individual qualifications and job performance. In all matters affecting employment, compensation, benefits, working conditions, and opportunities for advancement, we will not discriminate against any associate or applicant for employment because of race, religion, color, creed, national origin, citizenship status, sex, sexual orientation, gender identity and expressions, genetic information, marital status, age, disability, or status as a covered veteran.

In addition, we are committed to furthering the principles of Equal Employment Opportunity (EEO) through Affirmative Action (AA).

We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.

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