Data Scientist

Ecolab Food Safety & Hygiene Solutions Private Limited; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Ecolab Food Safety & Hygiene Solutions Private Limited is seeking a Data Scientist to turn raw operational data into actionable insights for the Institutional & Specialty segment. You will work across ML, GenAI, and agentic workflows to determine what matters and explain why, partnering with product, engineering, and business teams.

You will develop and deploy ML models, create dashboards, and build GenAI applications, with emphasis on production-readiness, monitoring, and cost efficiency.

Qualifications

• Bachelor's degree in Data Science, Computer Science, Math, Statistics, or a related field with hands-on data science experience or a Master's with relevant experience.
• 3+ years of Python; write clean, modular code with version control, testing, and code review.
• 3+ years of SQL experience for querying and preparing data.
• Hands-on PySpark and DataFrame APIs on a large-scale distributed platform.
• 2+ years building machine learning models (training, tuning, evaluation).
• Experience deploying data science/GenAI solutions to production with measurable impact.
• 1+ year building GenAI/LLM solutions, including RAG pipelines or agents.

Responsibilities

• Build, test, and deploy ML and analytical solutions (classification, forecasting, summarization, Q&A, recommendations).
• Train, tune, and evaluate models; defend choices with error analysis beyond single accuracy metrics.
• Create GenAI applications using LLM APIs and vector databases; integrate structured prompts and retrieval-augmented generation.
• Collaborate with product, engineering, and business teams; translate requirements into scalable data science solutions.

Skills

Python

SQL

PySpark

Data Visualization

GenAI

LLM

CI/CD

Git

Power BI

Education

Bachelor's in Data Science/CS/Math

Tools

Databricks

Spark SQL

Delta Lake

Unity Catalog

MLflow

LangChain

OpenAI API

Job description

Data Scientist Data Scientist Ecolab Digital is seeking a Data Scientist to help turn raw operational data into prioritized, plain-language insights and recommendations that reach customers in the Institutional & Specialty segment. You will join a team that pulls together diverse real-world signals, such as audits, inspections, sensor telemetry, checklists, and third-party sources, into one coherent view, then works across classical machine learning, LLM-based applications, and emerging agentic workflows to decide what matters and say why. Partnering with product, engineering, and business stakeholders, you will take problems from data exploration and modeling through deployment and monitoring, contributing production-grade components that customers and internal teams rely on to make decisions. You will apply established data science practice while learning and deploying the newer GenAI craft on real, customer-facing work.

What you will do

Build, test, and deploy analytical and machine learning solutions such as classification, forecasting, summarization, Q&A, recommendations, and decision support, using data from diverse internal and external sources. Train, tune, and evaluate machine learning models, and defend your choices with sound error analysis rather than a single accuracy number. Build GenAI applications on LLM APIs: structured prompts with output schemas, retrieval-augmented generation over vector indexes, and GenAI reasoning combined with deterministic logic for reliable, auditable outputs. Contribute to multi-step AI workflows for task and goals based agents. Prepare, structure, and validate datasets so data quality and model reliability are earned, not assumed. Deploy solutions into cloud environments using established engineering and CI/CD practices. Monitor deployed models and AI systems, and support performance, reliability, latency, and cost efficiency after launch. Build dashboards and visualizations that turn model output into decisions stakeholders can act on. Translate requirements from product, engineering, and business partners into scalable solutions, and communicate insights and impact clearly to technical and non-technical audiences.

Minimum Qualifications

• Bachelor's degree in Data Science, Computer Science, Math, Statistics, or a related field with 3 years of hands-on data science experience, or a Master's degree in a related field with 1 or more years of hands-on experience.
• 3+ years of Python. You write clean, modular code and treat version control, testing, and code review as standard practice.
• 3+ years of SQL for querying and preparing data.
• Hands-on experience with PySpark and DataFrame APIs on a large-scale distributed platform.
• 2+ years building machine learning models, covering training, tuning, and evaluation.
• Classical machine learning and statistics are central to this team, not replaced by LLMs. They are how we keep the LLMs honest, from anomaly detection to composite scoring.
• 1+ year building GenAI or LLM solutions, personal projects included. This means building RAG pipelines, agents, or applications.
• A strong side project or open-source contribution counts here as much as work experience.
• You should be able to show what you built and problem it solved.
• Experience taking models and solutions all the way to production. We are looking for someone who has gone past proofs-of-concept and personal experiments and shipped something real that other people depended on, then stayed with it through the iteration cycle of fixing, improving, and re-releasing.
• Tell us what you put into production, who used it, and what you changed after launch.
• A working sense of evaluation: can you prove a change actually made things better? When you adjust a prompt, a model, or a pipeline, you can measure whether the output genuinely improved rather than just confirming it still runs. That means comparing results against a trusted answer key, watching quality after launch, and keeping errors and hallucinations in check, especially in anything customer-facing.
• Working knowledge of Git, agile practices, and CI/CD workflows as a normal part of how you ship.
• Experience building dashboards and data visualizations to communicate results, Power BI preferred.
• Strong analytical thinking, problem-solving, and the ability to explain your approach, assumptions, and trade-offs to a range of stakeholders.
• Solid data science foundation that carries into GenAI work: EDA, statistical reasoning, metric and evaluation design, sampling, and error analysis.

Preferred Qualifications

• Experience on the Databricks platform: Spark SQL, Delta Lake, Unity Catalog, MLflow, Vector Search, and Model Serving.
• Hands-on experience with GenAI frameworks and tools: LangChain, Anthropic, OpenAI or Hugging Face APIs, and vector databases.
• Exposure to agentic or multi-step AI workflows such as tool-calling and sequential handoffs.
• Proficiency across the Microsoft Azure suite and comfort with cloud APIs across multiple environments.
• Experience in Retail or Quick Service Restaurant businesses.
• Sharing a public GitHub profile or project portfolio is encouraged; we would love to see examples of your hands-on work where available.