Senior Data Scientist - BOT (Build-Operate-Transfer)

Location: Bangalore

Experience: 10-12 Years

Industry Preference: Oil & Gas / Energy Sector

About the Opportunity:

We are building a high-performance Build-Operate-Transfer (BOT) data science team in India to support a global private equity firm's digital transformation initiatives. This role is ideal for experienced data science professionals who want to contribute to complex, high-impact projects within the energy sector.

The Senior Data Scientist will lead the design, development, and deployment of machine learning and AI solutions. This individual will work closely with cross-functional teams including data engineers, analysts, and business stakeholders to solve challenging problems in operational analytics, investment evaluation, and ESG reporting.

Role Overview:

As a Senior Data Scientist, you will take ownership of the end-to-end data science pipeline-ranging from ideation and data exploration to production model deployment and monitoring. You will apply your deep technical expertise and domain knowledge to develop innovative solutions that drive measurable business outcomes across portfolio operations.

Key Responsibilities:

Leadership & Strategy

- Define the data science roadmap and contribute to strategic planning and execution.

- Mentor junior team members and foster a culture of continuous learning and innovation.

- Collaborate with senior leaders to identify and prioritize high-value use cases.

Project Management

- Manage multiple data science initiatives, ensuring delivery of high-impact results.

- Translate business problems into data-driven solutions and success metrics.

- Partner with stakeholders to scope, plan, and implement projects within timeline and budget.

Technical Development

- Design, build, and deploy predictive models using advanced statistical and machine learning techniques.

- Apply data mining, time series forecasting, classification, regression, and optimization models to real-world problems.

- Work with structured and unstructured data using tools such as Python, R, SQL, TensorFlow, PyTorch, and Scikit-learn.

Data Infrastructure & Governance

- Collaborate with data engineering teams to ensure reliable data pipelines and feature stores.

- Promote data governance, model versioning, reproducibility, and MLOps best practices.

- Ensure responsible AI use, model explainability, and compliance with regulatory standards.

Innovation & Research

- Explore and pilot emerging AI/ML techniques relevant to the energy domain.

- Conduct proof-of-concepts and performance benchmarking for new models.

- Leverage domain-specific knowledge to enhance feature engineering and model interpretation.

Communication & Influence

- Present analytical findings and technical concepts to business and non-technical stakeholders.

- Develop dashboards, presentations, and documentation that support data-driven decision-making.

- Act as a bridge between technical teams and business functions to ensure alignment and impact.

Qualifications:

- Experience: 10-12 years in data science, with a proven track record of leading projects end-to-end.

- Domain Exposure: Prior experience in the energy sector, especially oil & gas, is highly preferred.

Technical Proficiency:

- Expert in Python, R, SQL, and machine learning frameworks like TensorFlow, PyTorch, Scikit-learn.

- Hands-on experience with cloud platforms (AWS, Azure, or GCP) and big data tools (e.g., Spark).

- Familiar with MLOps tools, version control, CI/CD pipelines, and model monitoring.

Soft Skills:

- Strong problem-solving, critical thinking, and stakeholder management abilities.

- Effective communicator with the ability to simplify complex technical topics.

- Demonstrated leadership and mentoring capabilities.

Education:

- Bachelor's, Master's, or PhD in Data Science, Computer Science, Engineering, Mathematics, or a related quantitative field.