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Well established Fintech Co. logo
Head Data Science
Well established Fintech Co.
Well established Fintech Co.'s logo

Head Data Science

at Well established Fintech Co.

Agency job
8 - 12 yrs
₹30L - ₹35L / yr
Delhi, Gurugram, Noida, Ghaziabad, Faridabad
Skills
skill iconData Science
skill iconPython
Artificial Intelligence (AI)
Google Vertex AI
Google Cloud Platform (GCP)

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.


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