Data Scientist
Hitachi Energy · Chennai · onsite · Posted 51d ago
Undisclosed1–6 yrsfulltimeSourced from
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About this role
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 youll 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 Energys core values safety and integrity, which means takingresponsibility for your own actions while caring for your colleagues and thebusiness.
Your background:
- Bachelors degree in computer science / data science, or quantitative discipline. 48 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.
Sourced from naukri
Skills
AgileData ingestionanalytical thinkingeltdata scientistazure mlai governanceAnalyticsdeploymentDatabricksAdvanced AnalyticsAzure Databricksdata analysiscomplianceData ProcessingETLMicrosoft AzureData ScienceArtificial Intelligence
About Hitachi Energy
Hitachi Energy
Power
2.5k+
employees
2019
7 years old
Zurich, Switzerland
CH
About
Hitachi Energy focuses on providing innovative solutions to enhance sustainability across power and digital systems, addressing the global push for a carbon-neutral future.
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