Sr Data Scientist Connected Assets 600 000 across 40 industries globally Digital Products Powered 13 WQ IQ CIP IQ Aqua IQ Dish IQ Pest Intelligence Kitchen IQ HX IQ and more Digital Revenue Enabled 370M annually Data Points Processed 250 billion per year from industrial IoT controllers Team Size 150 domain experts across 6 global locations Global Locations Pune India Naperville USA Jeddah Saudi Arabia and 3 additional sites Alarm Automation Rate 88 and growing through AIdriven transformation TVD Generated 22M in 2025 on track for 100M in 2026 EGIC 2 0 Transformation Context EGIC is undergoing a fundamental transformation from reactive operations EGIC 1 0 to an autonomous intelligence engine EGIC 2 0 through two strategic programs AIM AI Integration Modernization Embedding AI across all EGIC workflows automating reactive alarm triage building predictive intelligence and liberating 2530 FTEequivalent capacity through agentic automation APEX Adoption Proactive Engagement eXpansion Driving digital adoption converting hardwareonly customers to digital subscribers and scaling TVD from 22M to 100M through proactive customer engagement This role is central to both programs the candidate will lead the AI team that powers AIM and provides the intelligence backbone for APEX 3 Role Summary 3 1 The Prospect We are looking for a Sr AI Engineer a rare hybrid professional who combines deep business process understanding with advanced AI Data Science technical expertise and proven people leadership This individual will lead a team of 56 data scientists and AI engineers driving the daily AI operations project delivery model deployment adoption enablement and production triage across EGICs entire digital product portfolio The ideal candidate has walked a deliberate career path starting with understanding how business processes work BPA then building the AI that transforms those processes Data Science and now leading the team that operates scales and governs that AI at enterprise grade Leadership This combination ensures the candidate doesnt just build technically impressive models but builds the RIGHT models that solve REAL operational problems and deliver MEASURABLE business outcomes 3 2 What Makes This Role Unique You will lead AI operations for one of the largest industrial IoT intelligence centers in the world 600K connected assets 250B data points year Your models will directly impact water conservation energy efficiency and sustainability outcomes for customers across 40 industries globally You will have endtoend ownership from identifying the business problem BPA lens designing the AI solution DS lens deploying and scaling it Ops lens measuring its impact Leadership lens You will build and shape a team from a position of influence defining the culture technical standards and the operational playbook Direct visibility to EGIC Director and senior leadership your work directly drives strategic decisions and commercial outcomes 100M TVD target Cuttingedge technology Databricks Azure LLMs agentic AI RAG pipelines edge computing realtime IoT streaming 3 3 This Role Is NOT NOT a pure research academic role we need production engineers not just experimenters NOT a peopleonly management role you must be technically handson and review architecture decisions NOT a singleproject role you will manage a portfolio of 35 concurrent AI projects across different digital products NOT isolated from the business you will regularly interact with Operations Product Engineering Field and Customerfacing teams 4 Key Responsibilities 4A Business Process Analysis Operations Leadership Your BPA foundation differentiates this role from a typical Data Science lead You will use process analysis expertise to ensure every AI solution is grounded in a deep understanding of the operational workflow it serves AI without process understanding leads to technically impressive but operationally useless solutions i EndtoEnd Process Mapping Analysis Map all EGIC operational workflows across 13 digital products from data ingestion alarm generation triage insight creation customer delivery value capture TVD Identify human touchpoints decision nodes escalation paths and handoff points in each workflow Quantify time spent error rates and throughput at each process step to identify automation ROI Use BPMN Business Process Modeling Notation or equivalent tools to create standardized versioncontrolled process documentation ii Automation Opportunity Identification Systematically identify and prioritize automation candidates using a structured scoring framework Impact Feasibility Urgency Distinguish between rulebased automation RPA MLbased automation predictive models and agentic automation LLMpowered agents recommending the right approach for each use case Build

📌 Senior AI Engineer Data Science and Business Process Leadership (Pune)
🏢 Ecolab Food Safety & Hygiene Solutions Private
📍 Pune