Data Governance & Portfolio Enablement Specialist_GSO

Siemens Mobility; Gurugram District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

SIEMENS ENERGY INDIA LIMITED is seeking a Data Governance and Portfolio Enablement Specialist in India. The role analyzes large datasets, builds predictive models, and delivers insights to support strategic decisions while safeguarding governance across service units.

You will define data ownership, enable governed data products, and collaborate with product, IT, legal, and cybersecurity teams to advance metadata, quality, and data lineage practices for scalable data‑driven solutions.

Qualifications

• Bachelor’s or Master’s degree in data science, CS, statistics, mathematics or related field.
• 5–8+ years in data science or applied analytics.
• Strong communication and stakeholder management skills.
• Experience in global cross‑functional teams.
• Proficiency with Data Governance, Data Catalog, Metadata Management, Data Lineage, Snowflake, Power BI.
• Strong Python or R and data libraries (Pandas, NumPy, SciPy).
• ML frameworks (Scikit‑learn, TensorFlow, PyTorch).
• SQL experience and cloud data platforms (AWS, Azure, GCP).

Responsibilities

• Define and maintain data governance standards, policies, and procedures.
• Establish data ownership, stewardship, classification, and quality controls.
• Support digital portfolio intake, prioritization, and use‑case tracking.
• Enable creation and reuse of governed data products across domains.
• Collaborate with product, IT, legal, compliance, and cybersecurity teams.
• Drive metadata management, data lineage, and data quality initiatives.
• Enforce governed data approaches and data contracts across units.
• Surface reusable, governed data products for service units.
• Collect, explore, and analyze large datasets; develop predictive models.
• Train/validate models for classification, forecasting, or recommender systems.
• Write clean Python/R code; build data pipelines with engineers.
• Design and run A/B tests; apply statistics to validate hypotheses.
• Translate analyses into actionable recommendations for leadership.
• Stay updated on ML/AI trends and improve data science frameworks.

Skills

Data governance

SQL

Python

R

Power BI

Snowflake

Cloud platforms

ML frameworks

Communication

Stakeholder mgmt

Education

Bachelor’s or Master’s degree in data science or related field

Tools

Databricks

Tableau

Plotly

Job description

520081

01-Sep-2026

Research & Development

SIEMENS ENERGY INDIA LIMITED

Position Summary:

The Data Governance and Portfolio Enablement Specialist is responsible for analyzing complex datasets, developing predictive models, and generating actionable insights that support strategic decision‑making.

You must safeguard data governance across service business units and support Portfolio Management, so every initiative becomes a governed use case built on governed & owned data.

Ideal candidates shall have deep data-governance expertise (ownership, quality, classification), fluent portfolio & use-case management and strong cross-functional facilitation experience. Further you should be comfortable with modern data-product thinking — reusable, standardized data products & artifacts (datasets, models, pipelines) enriched with metadata, data contracts, quality rules, governance policies & SBOM, with ownership aligned to a domain or use case.

A Snapshot of your Day

How You’ll Make an Impact (responsibilities of role)

Strategic

• Define and maintain data governance standards, policies, and operational procedures.
• Establish data ownership, stewardship, classification, and quality controls.
• Support digital portfolio intake, prioritization, and use‑case tracking processes.
• Enable creation and reuse of governed data products across business domains.
• Collaborate with business, IT, legal, compliance, and cybersecurity partners.
• Drive metadata management, lineage, and data quality initiatives.
• Enforce governed data approaches — sources, contracts, reuse
• Settle data ownership early with domain & business owners
• Surface reusable, governed data products across service business units

Operational

1. Data Analysis & Insights

• Collect, explore, and analyze large datasets using statistical methods.
• Identify trends, correlations, and actionable insights to support business decisions.
• Communicate findings through clear visualizations, dashboards, and reports.
• Develop, train, and validate predictive models for classification, regression, clustering, time‑series forecasting, or recommendation systems.
• Perform feature engineering, feature selection, and model optimization.
• Employ ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Build and maintain data preprocessing and transformation pipelines.
• Work with data engineers to ensure reliable data availability and quality.
• Write clean, efficient code in Python or R for modeling and analysis logic.

4. Experimentation & Statistical Testing

• Design and run A/B tests or experimental studies.
• Apply statistical methods to validate hypotheses and measure impact.
• Ensure the integrity and rigor of analytical methodologies.

5. Collaboration & Business Integration

• Work closely with product managers, engineers, domain experts, and leadership teams.
• Translate complex analytical results into actionable recommendations.
• Support product development through data‑driven insights and modeling.

6. Research & Continuous Improvement

• Stay updated with emerging trends in ML, AI, data analytics, and tools.
• Experiment with new algorithms, technologies, and approaches.
• Contribute to improving internal data science frameworks and practices.

What You Bring (required qualification and skill sets)

• Bachelor’s or master’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, or related field.
• 5-8+ years of experience in data science or applied analytics.
• Strong communication and stakeholder management skills
• Experience working in global cross‑functional teams
• Data Governance Frameworks, Data Catalog Solutions, Metadata Management, Data Lineage, Snowflake, Power BI
• Strong experience with Python or R and data libraries (Pandas, NumPy, SciPy).
• Proficiency in ML frameworks (Scikit-learn, TensorFlow, PyTorch).
• Good understanding of statistical modeling, hypothesis testing, and experimental design.
• Experience working with SQL and cloud data platforms (AWS, Azure, GCP).
• Curious, detail‑oriented, and passionate about data‑driven solutions.
• Ability to explain technical results to non-technical stakeholders.

Preferred Qualifications

• Experience with big data tools (Spark, Databricks, Kafka, Hadoop).
• Familiarity with MLOps platforms (MLflow, Kubeflow, DVC).
• Knowledge of data visualization tools (Tableau, Power BI, Plotly).
• Background in time‑series forecasting, NLP, or computer vision.
• Experience in domain‑specific analytics (finance, IoT, geospatial, utility networks, etc.).
• Working experience with Snowflake, Power BI, Microsoft Fabric, Collibra