Data Scientist - GenAI - Consultant · Infosys Consulting - Europe

Fri, 24 Apr 2026 14:13:18 GMT
Engineering

Infosys Consulting - Europe · London · hybrid

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of over 320,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready?

The Role --------

We are looking for highly skilled Data Scientists to join our team. As a Data Scientist, you’ll design and deliver GenAI solutions (LLM/RAG) and applied ML components, taking prototypes through to production with strong evaluation, observability and governance. You will work closely with cross-functional teams, including data engineers, analysts, and business stakeholders, to turn data into actionable strategies that drive business outcomes.

Key Responsibilities --------------------

Design and deliver GenAI solutions including LLM/RAG (retrieval strategy, embeddings, vector stores, prompt flows, grounding) for enterprise use cases.

Evaluate and improve solution quality using offline/online metrics (quality, latency, cost) and iterate based on feedback.

Harden solutions for production with observability/monitoring, tracing, guardrails, safety controls, and reliability practices

Build and integrate model endpoints into products and workflows (APIs/services), partnering with engineering through to deployment.

Work across cloud platforms (Azure/AWS/GCP) integrating storage, compute, orchestration, and model/runtime components.

Assess data readiness for modelling/RAG (fitness, quality, access) and define remediation requirements

Collaborate in cross-functional squads (DS/DE/engineering/product) and contribute to reusable assets and ways of working.

Communicate clearly with stakeholders on trade-offs, evaluation results, risks, and adoption actions.

Own end-to-end workstream delivery, lead stakeholder conversations, mentor others. (more senior levels)

Shape solution direction and quality bar, coach teams, contribute to sales pursuits/bids and accelerators (most senior levels)

Requirements ------------

Essential Skills:

Strong Python/R (pandas/NumPy; ML libs such as scikit-learn; DL frameworks TensorFlow/PyTorch).

Experience with LLM/RAG toolchains (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector search (e.g., Pinecone, Weaviate, FAISS, Azure AI Search).

Experience with GenAI platforms (e.g., OpenAI API, Anthropic, Gemini, Llama or equivalents).

Exposure to big data/distributed computing and pipeline/feature engineering.

LLM safety & governance (hallucination mitigation, grounded responses, audit trails)

Degree in a quantitative field

Right to work in the UK without sponsorship

Preferred Skills:

Cloud ML experience (AWS/GCP/Azure).

Strong SQL; experience with visualisation tools (Tableau/Power BI or Python viz).

Specialisms: NLP / computer vision / time series.

NoSQL familiarity.

Quant / trading analytics engineering practices

Time-series forecasting (prices, demand, blend outcomes, scheduling effects)

Optimisation / simulation (planning, blending, logistics constraints)

Model risk controls (bias/leakage checks, backtesting discipline, monitoring/drift)

CI/CD, deployment, monitoring; Docker/Kubernetes.

Experiment design and randomised trials.

MSc with PhD a plus

Personal attributes

Analytical, pragmatic problem-solver; outcome-oriented.

Self-directed, able to prioritise and juggle multiple workstreams.

Clear communicator who can simplify complexity.

Collaborative, curious, continuous learner.