Data Scientist

Hitachi ABB Power Grids; Chennai District; On-site; INR 1,600,000 - 3,200,000; Full time

Job summary

Hitachi Energy is seeking an Engineering Data Scientist to join Indian Operation Center (INOPC-PG) in Chennai. You will drive ML initiatives, build scalable models, and collaborate with data engineers to ensure high-quality data pipelines and prescriptive insights for business optimization.

You will work with tools like Databricks, Azure Synapse, Power BI and Python to deliver executive-level insights and ensure governance and ethical AI practices.

Qualifications

• Bachelor's degree in computer science / data science or quantitative field.
• 4–8 years of progressive experience in data science and analytics.
• Strong SQL and data engineering fundamentals; ability to design scalable pipelines.

Responsibilities

• Drive technical excellence in data science with high-impact ML initiatives.
• Design and deploy advanced ML models and prescriptive frameworks for business insights.
• Collaborate with data engineers to build robust data pipelines and feature stores.
• Ensure model performance, transparency, and governance with best practices.
• Leverage Power BI and Python to visualize model outputs for executives.
• Provide end-to-end data science solutions with measurable ROI.

Skills

Data Science

Machine Learning

Python

SQL

Power BI

Azure Databricks

MLOps

Team collaboration

Education

Bachelor's degree in Computer Science / Data Science or quantitative discipline

Tools

Databricks (PySpark/Spark SQL)

Power BI

Azure Databricks

Synapse

ADF

Azure ML Studio

Pandas

NumPy

Scikit-Learn

Job description

As an Engineering Data Scientist, you will be part of Indian Operation Center, India(INOPC-PG), aiming to develop a global value chain, where key business activities,resources, and expertise are shared across geographic boundaries to optimize valuefor Hitachi Energy customers across markets. As part of Transformers BU, we providehigh-quality engineering and Technology to Hitachi Energy world. This is an important step from Hitachi Energy's Global Footprint strategy.

How you’ll make an impact:

Drive technical excellence in Data Science by spearheading high-impact MLinitiatives within a cross-functional team of engineers and analysts.

Design and deploy advanced machine learning models and predictiveframeworks, moving beyond descriptive reporting to provide foresight intobusiness trends.

Analyze high-dimensional datasets to extract latent patterns and deliverprescriptive recommendations that drive strategic business optimization.

Partner with Data Engineers to architect robust pipelines and feature stores,ensuring high-quality data ingestion for model training and inference.

Ensuring model transparency, performance stability, and adherence to ethicalAI governance and best practices.

Leverage tools like Power BI and Python to visualize complex model outputs,making machine learning results interpretable for executive decision-making.

Collaborate with business units to identify challenges solvable through AI,proposing end-to-end Data Science solutions that deliver measurable ROI.

Proactively troubleshoot and refine ML models, addressing data drift andperformance degradation to maintain long-term accuracy and scalability.

Responsible to ensure compliance with applicable external and internal regulations, procedures, and guidelines.

Living Hitachi Energy's core values safety and integrity, which means takingresponsibility for your own actions while caring for your colleagues and thebusiness.

Your background:

Bachelor's degree in computer science / data science, or quantitative discipline. 4-8 years of progressive experience in Data Science and Advanced Analytics.

Extensive experience in Statistical Modeling and Machine Learning, includingdeep understanding of supervised/unsupervised learning, feature engineering,and model validation.

Expert-level proficiency in Complex SQL and architecting scalable ETL/ELTpipelines to handle high-volume, unstructured, and structured datasets.

Hands-on experience with Databricks (PySpark/Spark SQL) for large-scale data processing and Microsoft Power BI for delivering executive-level prescriptiveinsights. Should have Strong Domain Knowledge across the Data Science

Experience in Azure Databricks, Synapse, ADF, Azure ML Studio. Proficient in Python (Scikit-Learn, Pandas, NumPy) and seasoned in MLOpsprinciples (model versioning, deployment, and monitoring) within an Agileframework. Ability to independently manage end-to-end BI projects.

Strong analytical and problem-solving skills with a focus on data accuracy andperformance optimization.Ability to collaborate effectively across engineering and business teams fromdifferent cultural and geographical backgrounds.

Strong analytical skills, experience in data analysis and management. Ability to work independently and as part of a team.

Detail-oriented with the ability to manage multiple tasks simultaneously.Ability to manage multiple priorities and meet deadlines. Tasks and time self-management.

Proficiency in both spoken & written English language is required.

Job function Data Analytics | Warehousing & Business Intelligence

Contract Regular

Publication date 2026-08-27

Reference number R0121735

About Hitachi Energy

We are a global leader in electrification, powering the electricity era to meet the energy demands of today, and the next 25 years. As the energy arm of Hitachi Group, over three billion people depend on our pioneering, mission-critical technologies to power their daily lives.

With over a century of innovation, we are addressing the most urgent energy challenge of our time: driving the evolution of the world's energy system to ensure abundant, secure, affordable, and sustainable power for today’s generation and the next.

With an unparalleled installed base in over 140 countries, we are the grid ecosystem partner across the utility, industry, data center, and transportation sectors. Headquartered in Switzerland, we employ over 56,000 people in 60 countries and generate revenues of around $20 billion USD.