Head of Data Science, India GSC

Job Title: Head of Data Science, India GSC

We are looking for a principal-level developer who still wants to build and cares deeply about design. You will develop the user experience, APIs and supporting services for an internal platform that helps people across Asset Management understand the data behind business processes and improve its quality. Based in the Data and Analytics Office, you will work closely with business users and collaborate with data, AI and Technology colleagues to turn ideas into useful software. Technology leads production deployment and ongoing service operation, so you will build in partnership with them to the standards required for a secure, scalable and supported product.

In this role, you will

This role suits you if you

build complete web applications with modern TypeScript front ends (whether Angular, React or Vue) and Python services behind them, deployed through pipelines to the cloud;

have shipped applications to production that people use, and can show the results; • care about design as much as code, and simplifying things is your instinct;

are comfortable developing within a business-led data team while collaborating closely with Technology to bring applications into production;

have a history of building and launching things, at work or in your own time, and a portfolio that shows it.

It is unlikely to suit you if your recent role has been mainly architecture or oversight rather than hands-on coding, if you have not built Python back-end services, or if you have worked on only one side of the stack. Experience beyond the core profile is welcome, but it cannot replace it.

Build data applications end to end

Design and build the platform from interface to data layer, including TypeScript front ends (Angular or React), Python services and APIs (FastAPI ), and the data access, integration and transformation code behind them.

Translate loosely defined business and user needs into pragmatic designs and working software, iterating with users from prototype to pilot and, with Technology, into supported production services.

Architect for scale and change with clean service boundaries, performance under real load, and code that stays easy to extend as the platform grows.

Work with Technology colleagues on cloud deployment (Google Cloud), automated CI/CD pipelines, monitoring and the requirements for a secure and supported production service.

Build reusable components, API patterns and templates that make each subsequent platform capability faster to deliver.

Design experiences people want to use

Own UX and UI end to end. Understand business users' needs, sketch and test flows, and take designs from wireframe to polished interface without depending on a separate design team.

Simplify relentlessly, turning business processes, metadata, ownership, lineage, data-quality rules and exceptions into clear, intuitive views, and personalise experiences to each user's role and needs.

Design iteratively, using usage analytics and user feedback to measure engagement and refine what works.

Establish a design system and front-end patterns, built to accessibility standards (WCAG 2.2 AA).

Work with data , technology and AI colleagues

Work with Data Architecture and Governance and Data Product Owners so platform capabilities reflect agreed data models, definitions, ownership and controls.

Partner closely with Technology architects, engineers and service colleagues on solution design, integration, security, deployment and support. Technology will lead production readiness, controlled release and ongoing service operation.

Bring the work of data scientists and AI specialists into the platform where it adds value, with appropriate APIs, guardrails and telemetry.

Lead agentic development practice

Build day to day with GitHub Copilot and Claude Code, working in a spec-first way. Agree the plan, let agents implement in small increments, then review, test and refine.

Set up and maintain the team's AI development workflow, including repository instruction files (for example CLAUDE.md, AGENTS.md or Copilot custom instructions), reusable agent skills, custom agents and subagents, and MCP connections to approved tools. 3 PUBLIC

Build guardrails into the workflow, such as hooks and CI checks that enforce tests, linting and security scanning on AI generated code, and make sure no confidential data leaves approved boundaries.

Mentor colleagues in using these tools with judgement, including recognising when an agent's output should not be trusted.

Engineer to production standard

Work within the bank's software development lifecycle, including version control, code review, automated testing, CI/CD, security scanning, clear API specifications (OpenAPI) and documentation.

Design for enterprise requirements from the outset, including authentication and authorisation , auditability, resilience and supportability, and meet data protection, information security and AI risk requirements.

Agree engineering standards, interfaces and production requirements with Technology colleagues so capabilities developed within the Data and Analytics Office can be deployed and supported through Technology-led processes.

Set development standards and reference patterns for colleagues contributing to application development, lead design and code reviews, and mentor others to deliver to a consistent standard.

To be successful you will

You should be able to evidence all of the following, through your portfolio and from roles in the last few years.

A track record of shipping web applications to production that real users adopted, with evidence of usage or engagement.

Experience at senior, staff, principal or lead level while remaining an active developer, with most of your recent time spent designing and writing code.

Expert TypeScript front-end development in at least one modern component framework (we use Angular and React; Vue is also relevant), with the depth to move comfortably between them, including state management, component design, testing

and performance.

Production experience building and securing Python APIs, ideally with FastAPI (Flask or Django also relevant), including Pydantic validation, asynchronous programming and API design.

Strong UX and UI design ability, shown through interfaces that make complex workflows or data simple to use, and the ability to design and prototype your own interfaces.

Well-architected, scalable code with sound application design, performance tuning and code that others can maintain.

Advanced SQL, data modelling and experience integrating multiple data sources and APIs into a coherent application.

Hands-on cloud experience (Google Cloud, Azure or AWS), including Docker, deploying through CI/CD pipelines, and running applications in production.

Engineering discipline covering Git, code review, automated testing (for example pytest, Playwright or framework test tools) and secure coding, including OAuth 2.0 and OpenID Connect.

Hands-on use of agentic coding tools (for example Claude Code, GitHub Copilot or Cursor) beyond autocomplete, including planning work for agents, giving them the right context through instruction files, skills or custom agents, and reviewing and testing what they produce.

A working understanding of metadata, data lineage, data quality and semantic layers, and why they matter to users.

Experience collaborating across business-led data teams and Technology to move software from rapid development into secure, supported production services.

Clear written and spoken English, and confidence working with senior stakeholders across time zones.

Exceptional design for data applications. You make dense, complex information feel simple and obvious, and your interfaces are as polished as they are useful.

Iterative, evidence-led design. You test with users, instrument usage and refine designs based on how people actually behave.

Personalisation. You have built experiences that adapt to a user's role, preferences or behaviour.

Code built to last. You have designed applications that scaled in users, data and features without being rewritten.

Measurable impact. You can point to growth in adoption or engagement that your work drove.

Also useful, but not essential - graph and relationship visualisation (for example React Flow, Cytoscape.js or D3), knowledge graphs, data catalogue or lineage tools, building LLM-enabled applications, Google Cloud specifically, and experience in financial services or another regulated environment.

By month 3 - a first improved user or a related data-- facing platform journey is live with real users, supporting business quality workflow and built on agreed front

By month 6 - end and API patterns. process onboarding reusable design and engineering patterns support faster, more consistent delivery, with the Data and Analytics Office and Technology working together to move prioritised capabilities through testing, controlled release and production support.

By month 12 - the platform supports wider use across Asset Management, with evidence of rising adoption and engagement, and contributing teams are shipping to shared development standards with sustainable Technology-led production and service arrangements.

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You’ll achieve more at HSBC

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”

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