Senior Data Scientist

Overview

The Senior Data Scientist builds and delivers AI-powered agents and agentic workflows that address business challenges. The role combines applied data science with hands-on delivery of scalable, secure and compliant AI solutions in enterprise environments.

What you'll do

• Lead the design, development and testing of single-agent and multi-agent solutions using LLMs, prompt and context engineering, retrieval-augmented generation (RAG), tool use and structured outputs.
• Translate business problems into agent goals, workflow logic, system interactions, acceptance criteria, exception handling and human-in-the-loop controls.
• Integrate agents with enterprise platforms, APIs, MCP servers, databases, SaaS applications and governed data sources.
• Build and optimise retrieval, grounding, memory and orchestration patterns.
• Establish evaluation and observability practices covering quality, groundedness, safety, latency, cost, failure modes and regression testing.
• Productionise solutions through source control, automated testing, deployment, release validation, monitoring, issue triage and continuous optimisation.
• Frame business problems as analytical, statistical, machine learning or agentic AI use cases, selecting the simplest effective approach.
• Prepare structured and unstructured data and perform feature engineering, model development, validation and error analysis using reproducible Python and SQL workflows.
• Design experiments and measurement approaches to demonstrate model performance, incremental value and business impact.
• Partner with Product, Engineering, Security, Legal, Compliance and business teams to define priorities, dependencies, controls and acceptance criteria.
• Embed responsible AI practices, including access controls, privacy protections, guardrails, human oversight, fallback mechanisms and audit-ready logging.
• Drive engineering and analytical standards through modular design, code quality, peer review, testing discipline and clear documentation.
• Communicate implementation choices, analytical findings, limitations, delivery risks and production readiness to technical and non-technical stakeholders.
• Provide technical guidance and contribute reusable patterns, evaluation assets and delivery standards across Data & Analytics.

What you'll need

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative field.
• 6+ years of experience in data science, machine learning, applied AI or software engineering, including delivery of production solutions.
• Hands-on experience building LLM-powered applications or agents using prompt and context engineering, RAG, tool or function calling, orchestration and structured evaluation.
• Experience implementing multi-step workflows with enterprise integrations, exception handling, state management and human-in-the-loop activities.
• Strong Python and SQL skills, with experience writing maintainable, testable and reusable code.
• Experience integrating applications with APIs, databases, vector stores, cloud services and enterprise data sources.
• Experience operationalising AI or machine learning solutions through Git-based source control, CI/CD, testing, deployment, monitoring and ongoing optimisation.
• Working knowledge of statistical modelling, machine learning, experimental design and model validation.
• Ability to deliver complex solutions with limited oversight and collaborate effectively across technical and business teams.
• Strong understanding of RAG, tool use, orchestration, memory, structured outputs, context engineering and agent evaluation.
• Strong grounding in data exploration, feature engineering, statistical reasoning, machine learning, experimentation and validation.
• Ability to build production-quality Python and SQL solutions and integrate them with governed enterprise systems.
• Familiarity with version control, testing, deployment pipelines, observability, monitoring and release management.
• Ability to design controls for privacy, safety, transparency, data protection, auditability and human oversight.
• Ability to structure ambiguous problems, make evidence-based trade-offs and lead delivery across functions.

Nice to have

• Master’s degree.
• Experience with Anthropic Claude and AWS Bedrock, including model access, knowledge bases, agents, guardrails and enterprise integrations.
• Experience building enterprise agents with Microsoft Copilot or Copilot Studio and connecting them to Microsoft 365, Power Platform or business applications.
• Experience using Claude Code and GitHub Copilot to accelerate software development while maintaining code quality and engineering controls.
• Experience with LangChain, LangGraph or similar orchestration frameworks, and Langfuse or comparable evaluation and observability tooling.
• Experience with vector databases, semantic search, document processing, multi-agent patterns and adversarial or red-team testing.
• Experience applying predictive modelling, natural language processing, optimisation, time-series forecasting or recommendation methods.
• Relevant agentic AI, generative AI, AWS, data science, machine learning, MLOps or responsible AI certifications.

Details

• Location: Hyderabad, Telangana, India.
• 100% in office.
• Minimal travel required.
• Work in a clean, pleasant and comfortable office work setting.