Data Scientist

Description

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 value for Hitachi Energy customers across markets. As part of Transformers BU, we provide high-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 ML initiatives within a cross-functional team of engineers and analysts.

• Design and deploy advanced machine learning models and predictive frameworks, moving beyond descriptive reporting to provide foresight into business trends.

• Analyze high-dimensional datasets to extract latent patterns and deliver prescriptive 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 ethical AI 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 and performance 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 taking responsibility for your own actions while caring for your colleagues and the business.

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, including deep understanding of supervised/unsupervised learning, feature engineering, and model validation.

• Expert-level proficiency in Complex SQL and architecting scalable ETL/ELT pipelines 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 prescriptive insights. 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 MLOps principles (model versioning, deployment, and monitoring) within an Agile framework. Ability to independently manage end-to-end BI projects.

• Strong analytical and problem-solving skills with a focus on data accuracy and performance optimization. Ability to collaborate effectively across engineering and business teams from different 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.

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