Job Title : Head of Data Science

Experience : 7+ years

Location : Gurgaon

Reporting : Top Management (CXO Level)

Role Overview :

We are looking for a visionary and hands-on Head of Data Science and AI with at least 6 years of experience to lead our data strategy and analytics initiatives. In this pivotal role, you will take full ownership of the end-to-end technology stack, driving a data-analytics-driven business roadmap that delivers tangible ROI. You will not only guide high-level strategy but also remain hands-on in model design and deployment, ensuring our data capabilities directly empower executive decision-making.

If you are passionate about leveraging AI and Data to transform financial services, we invite you to lead our data transformation journey.

Key Responsibilities :

Strategic Leadership & Roadmap :

- End-to-End Tech Stack Ownership : Define, own, and evolve the complete data science and analytics technology stack to ensure scalability and performance.

- Business Roadmap & ROI : Develop and execute a data analytics-driven business roadmap, ensuring every initiative is aligned with organizational goals and delivers measurable Return on Investment (ROI).

- Executive Decision Support : Create and present high-impact executive decision packs, providing actionable insights that drive key business strategies.

Model Design & Deployment (Hands-on) :

- Hands-on Development : Lead by example with hands-on involvement in AI modeling, machine learning model design, and algorithm development using Python.

- Deployment & Ops : Oversee and execute the deployment of models into production environments, ensuring reliability, scalability, and seamless integration with existing systems.

- Leverage expert-level knowledge of Google Cloud Agentic AI, Vertex AI and BigQuery to build advanced predictive models and data pipelines.

- Develop business dashboards for various sales channels and drive data driven decision making to improve sales and reduce costs.

Governance & Quality :

- Data Governance : Establish and enforce robust data governance frameworks, ensuring data accuracy, security, consistency, and compliance across the organization.

- Best Practices : Champion best practices in coding, testing, and documentation to build a world-class data engineering culture.

Collaboration & Innovation :

- Work closely with Product, Engineering, and Business leadership to identify opportunities for AI/ML intervention.

- Stay ahead of industry trends in AI, Generative AI, and financial modeling to keep Bajaj Capital at the forefront of innovation.

Must-Have Skills & Experience :

Experience :

- At least 7 years of industry experience in Data Science, Machine Learning, or a related field.

- Proven track record of applying AI and leading data science teams or initiatives that resulted in significant business impact.

Technical Proficiency :

- Core Languages : Proficiency in Python is mandatory, with strong capabilities in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.

- Cloud Data Stack : Expert-level command of Google Cloud Platform (GCP), specifically Agentic AI, Vertex AI and BigQuery.

- AI & Analytics Stack : Deep understanding of the modern AI and Data Analytics stack, including data warehousing, ETL/ELT pipelines, and MLOps.

- Visualization : PowerBI in combination with custom web/mobile applications.

Leadership & Soft Skills :

- Ability to translate complex technical concepts into clear business value for stakeholders.

- Strong ownership mindset with the ability to manage end-to-end project lifecycles.

- Experience in creating governance structures and executive-level reporting.

Good-to-Have / Plus :

- Domain Expertise : Prior experience in the BFSI domain (Wealth Management, Insurance, Mutual Funds, or Fintech).

- Certifications : Google Professional Data Engineer or Google Professional Machine Learning Engineer certifications.

- Advanced AI : Experience with Generative AI (LLMs), RAG architectures, and real-time analytics.

Education : B.Tech / B.E. / MCA / M.Sc or equivalent in Computer Science, Statistics, Mathematics, or Data Science.