Role Overview

At Haber, we are changing how industries run by combining automation with intelligent decision making. As a

Senior Data Scientist, you will build and own the machine learning systems behind our products - Elixa, Kaiznn,

Mount Fuji and our upcoming Fibre Morphology solution.

You will work with time-series sensor data coming from live plants, and build models for quality prediction,

process optimisation, anomaly detection, forecasting and root cause analysis. You will also lead a small team of 2

to 4 data scientists and set the technical direction for how we build and deploy models.

This is a hands-on leadership role. Our models do not stay in notebooks. They run in operating plants, where a wrong prediction costs real money, water and energy. We are looking for someone who has built a model, put it in production, seen it degrade, and fixed the system behind it.

Key Responsibilities

Build AI and ML solutions for quality prediction, process optimisation, anomaly detection, forecasting, root cause analysis and decision support

Work with time-series sensor data from live plants, and handle the real problems that come with it - sensor drift, missing data, changing conditions and limited labels

Own the full lifecycle: data collection, cleaning, feature engineering, model building, validation, explainability,

deployment and monitoring

Take models into production and keep them healthy - pipelines, versioning, monitoring, drift detection,

retraining and rollback

Own the technical direction for the data science team and decide what gets built, what gets reused and what gets retired

Lead and mentor 2 to 4 data scientists through code reviews, design reviews and day-to-day guidance

Contribute to AI system design - data access layers, model services, APIs and cloud deployment on AWS

Build optimisation and recommendation layers that act on model output in real time,



such as setpoint recommendation for plant operations

Work on Generative AI and Agentic AI solutions using LLMs, RAG, tool calling and knowledge graphs, as these become part of our product

Work closely with domain experts, product, software, cloud and engineering teams to turn industrial problems into working solutions

Stay current with research in machine learning, signal processing and industrial optimisation

Must Have

8 to 10 years of experience in Data Science and Machine Learning, with real production experience

Bachelors or Masters in Engineering, Computer Science, Data Science, Mathematics, Statistics or a related field

Solid Python and SQL, with Pandas, NumPy and Scikit-learn

Strong foundation in statistics, probability, mathematics and optimisation

Strong experience in time-series analysis and forecasting - this is the core of our work

Machine learning: regression, classification, clustering, anomaly detection and ensemble models

Proven experience deploying and maintaining models in production, including monitoring, drift detection and retraining

MLOps and production tools: Docker, Git, CI/CD, MLflow, FastAPI or similar

AWS for deployment and monitoring - S3, Lambda, SageMaker, CloudWatch

Working knowledge of deep learning using PyTorch or TensorFlow, especially for time-series problems

Model explainability using SHAP, feature importance or similar methods

Haber - Senior Data Scientist Page 1 Experience mentoring or leading other data scientists





Ability to work independently and take a project from idea to production

Good communication skills and comfort working with people who are not data scientists

Good to Have

Experience in manufacturing, chemicals, pulp and paper, water, energy, pharma, metals or similar industrial and process environments

Generative AI: LLMs, prompt engineering, RAG, embeddings and vector databases

Agentic AI: multi-agent systems, tool and function calling, and Model Context Protocol (MCP)

LangGraph, LangChain or similar frameworks; Knowledge Graphs or Neo4j

AWS Bedrock and RDS

Computer vision: image preprocessing, object detection, classification, segmentation, OpenCV, YOLO, CNNs or Vision Transformers

Optimisation, control theory, reinforcement learning or operations research

Signal processing fundamentals

Causal analysis, industrial digital twins, or AI governance and ISO 42001 exposure

Experience building system design, APIs and microservices for production AI systems

What We Offer

Real-World Impact: Your models will run in operating plants, not just in experimental labs

Ownership and Autonomy: Freedom to explore, decide and build in a high-trust environment

Leadership: A small team from day one, with room to grow into wider data science leadership

Diverse Tech Stack: Time-series, sensor data, vision, optimisation and generative AI in one place

Fast-Track Learning: A startup where learning never stops and innovation is constant

Collaborative Culture: A team that supports initiative, experimentation and personal growth

Product-Minded Thinking: Your work will be closely tied to product and business decisions

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Data Scientist (Pune)
🏢 Haber
📍 Pune