Data Scientist Vice President
At a glance
VP-level Data Science role at Citi. Bangaluru Karnataka India · full-time.
Pay not stated Data Science salary
dataroles summary, based on the employer's posting.
What you'll do
- Build AI applications such as copilots, knowledge assistants and workflow tools for supplier and vendor risk teams
- Create document ingestion and retrieval pipelines, then test and tune them to improve search results
- Develop Python backend services and APIs that connect AI capabilities with internal platforms and applications
- Put AI solutions into production while supporting governance, security, monitoring and auditability
- Work with business and technical teams to find AI opportunities and guide junior engineers
What you bring
- A bachelor's degree in computer science, engineering, mathematics or a related discipline
- Substantial experience across software engineering, AI engineering, analytics or data science
- Strong Python skills and a track record building REST APIs and backend applications
- Working knowledge of SQL, data engineering concepts, cloud platforms and enterprise application development
Who this fits
This VP-level role suits an experienced engineer who can take AI work from initial design through production and work with both technical and business partners. The position is hybrid in India, based in an office setting, with minimal travel.
From the employer
We are looking for an experienced AI Engineer to design, develop, and deploy enterprise-grade AI solutions that transform how Third-Party Management teams assess, monitor, and manage supplier and vendor risks.
This role combines software engineering, AI engineering, analytics, and product development to build intelligent applications that improve operational efficiency, decision quality, and user experience. The successful candidate will partner closely with business stakeholders, data engineers, technology teams, and AI governance partners to deliver scalable AI capabilities aligned with enterprise standards.
Key Responsibilities
AI Solution Development
- Design and build enterprise AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures.
- Develop AI-powered copilots, knowledge assistants, workflow automation, and decision-support tools.
- Build reusable AI services, APIs, and components for enterprise adoption.
- Develop multi-agent workflows for complex business processes.
Knowledge Engineering
- Design enterprise knowledge repositories using vector databases and knowledge graphs.
- Build document ingestion, metadata extraction, semantic search, and retrieval pipelines.
- Improve retrieval quality through evaluation and continuous optimization.
- Ensure knowledge assets remain governed, traceable, and reusable.
Software Engineering
- Build scalable Python-based backend services and APIs.
- Develop modern web applications using enterprise UI frameworks.
- Integrate AI services with internal data platforms and enterprise applications.
- Write clean, modular, and production-ready code.
AI Governance
- Ensure AI solutions comply with enterprise governance, security, and model risk requirements.
- Support model evaluation, monitoring, auditability, and explainability.
- Collaborate with AI governance teams on documentation and deployment approvals.
Collaboration
- Partner with business stakeholders to understand challenges and identify AI opportunities.
- Work closely with technology, architecture, cybersecurity, and data engineering teams.
- Support production deployment and operationalization of AI solutions.
- Mentor junior engineers and contribute to AI engineering best practices.
Required Qualifications
- Bachelor’s degree in computer science, Engineering, Mathematics, or related discipline. Master’s degree preferred.
- Significant experience in software engineering, AI engineering, analytics, or data science.
- Strong Python programming skills.
- Experience building REST APIs and backend applications.
- Knowledge of SQL and data engineering concepts.
- Experience working with cloud platforms and enterprise application development.
- Strong problem-solving and stakeholder management skills.
- Excellent written and verbal communication.
Preferred Qualifications
Experience in one or more of the following:
- LLM application development
- Retrieval-Augmented Generation (RAG)
- Agentic AI frameworks
- Prompt engineering
- Vector databases
- Knowledge Graphs
- AI orchestration frameworks
- Enterprise AI platforms
- Model evaluation frameworks
- MLOps or LLMOps
- Kubernetes
- CI/CD
- Banking, financial services, or risk management
Technical Skills
Programming
- Python
- SQL
- JavaScript/TypeScript (preferred)
AI & Machine Learning
- LLM applications
- RAG
- Embeddings
- Prompt engineering
- AI Agents
- NLP
Frameworks
- Google ADK
- OpenAI APIs
- Model Context Protocol (MCP)
Data Technologies
- PostgreSQL
- Vector databases
- Knowledge Graphs
- Neo4j
- Redis
Engineering
- FastAPI
- REST APIs
- Git
- Docker
- Kubernetes
- CI/CD
Leadership Expectations
- Demonstrate ownership from concept through production deployment.
- Drive innovation while maintaining engineering excellence.
- Communicate effectively with technical and non-technical stakeholders.
- Promote responsible AI practices and continuous learning.
- Foster collaboration across global, cross-functional teams.
•Working Environment: office setting, minimal travel required.
• Effort: minimal physical effort required.
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Job Family Group:
Decision Management------------------------------------------------------
Job Family:
Specialized Analytics (Data Science/Computational Statistics)------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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