Data Scientist

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. 

The ideal candidate should have a strong background in applied ML and GenAI delivery (LLM/RAG), including evaluation, deployment, and governance in production environments.

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

Skills and Qualifications: 

Essential Skills: 

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