Data Scientist

The opportunity:

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.