Responsibilities: · Partner with product and business stakeholders to translate ambiguous asks into clear AI/ML use cases · Own product relationships for assigned use cases by managing expectations, surfacing risks early, and aligning stakeholders around tradeoffs and business outcomes · Lead exploratory analysis, feature engineering, model selection, experiment design, and statistical validation for time series, forecasting, anomaly detection, and other IoT-oriented use cases · Work with IoT and sensor-based data, including irregular intervals, missingness, and event-driven signals · Define strong baseline approaches and recommend the simplest effective solution · Build and evaluate predictive, optimization, and GenAI-enabled solutions using reproducible workflows in Databricks · Help define and deliver data products that are reusable, maintainable, and valuable to downstream users, systems, or business processes · Use GitHub and Azure DevOps with strong version control, pull request discipline, documentation, and work tracking practices · Contribute to API-oriented solution design by shaping model inputs/outputs, integration expectations, and consumption patterns for downstream applications · Mentor junior and mid-level data scientists and contribute reusable templates and team standards Skills: · 6+ years of experience in data science, machine learning, or applied AI with a track record of delivering business-impacting solutions · Strong programming skills in Python, PySpark, and SQL · Solid grounding in statistics, machine learning, experimentation, and model evaluation · Hands-on experience with Databricks for exploratory analysis, model development, and reproducible ML workflows; familiarity with MLflow is strongly preferred · Demonstrated experience with time series modeling, forecasting, anomaly detection, and/or sequential data problems · Experience working with IoT, sensor, telemetry,



or other operational data sources · Strong data engineering capability, including data wrangling at scale, feature pipeline design, dataset preparation, data quality troubleshooting, and support for production-ready analytical workflows · Experience creating data products or analytics products intended for repeated use · Experience designing baselines, features, evaluation frameworks, and error analysis approaches for real-world AI/ML use cases · Strong ability to work across GitHub and Azure DevOps workflows, including pull requests, version control, and delivery tracking · Demonstrated ability to communicate clearly with technical and non-technical stakeholders and to influence product decisions with evidence · Experience partnering cross-functionally with engineering, product, and business teams to move from problem framing to production decision-making Preferred Skills: API design and integration, model monitoring, mentoring experience, familiarity with cloud-native deployment patterns A trusted partner at nearly three million customer locations, Ecolab (NYSE:ECL) is a global sustainability leader offering water, hygiene and infection prevention solutions and services that protect people and the resources vital to life. Building on a century of innovation, with an annual sales of $15 billion and more than 48,000 associates, Ecolab delivers comprehensive science-based solutions, data-driven insights and world-class service to advance food safety, maintain clean and protected environments, and optimize water and energy use, and improve operational efficiencies and sustainability for customers in the food, healthcare, life sciences, hospitality and industrial markets in more than 170 countries around the world. When you come to work at Ecolab, you get to take on some of the world’s most meaningful challenges and have the opportunity to learn and grow, shape your career, make an impact and quickly see the importance of your work.

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📌 Sr Data Scientist (Bengaluru)
🏢 (IND) Ecolab Global Services Private
📍 Bengaluru