Introduction
At IBM Consulting UK FutureNow, you’ll build a career at the forefront of hybrid cloud and AI, working with leading clients across the public and private sectors.
You’ll collaborate with top industry professionals, gain hands on experience with cutting edge technologies, and deliver solutions that create real business impact. From day one, you’ll work on meaningful, high profile programmes that stretch your skills and accelerate your growth.
We invest heavily in you–supporting continuous learning, in demand skills development, and long term career progression. You’ll thrive in a flexible, inclusive environment that values curiosity, encourages reinvention, and recognises what makes you unique.
We offer:
Tools and policies to support your work-life balance from flexible working approaches, sabbatical programs, paid paternity leave, maternity leave and an innovative maternity returners scheme
More traditional benefits, such as 25 days holiday (in addition to public holidays), private medical, dental & optical cover, online shopping discounts, an Employee Assistance Program, life assurance and a group pension plan through salary sacrifice.
Your role and responsibilities
As a Consulting Data Scientist, you will play a key role in the design, development, and deployment of Artificial Intelligence solutions across a range of client engagements.
Working as part of IBM Consulting’s Hybrid Cloud & Data practice, you’ll help clients unlock value from modern AI technologies, combining data science, machine learning, Generative AI, and Large Language Models to solve complex business challenges across public sector, financial services, and regulated industries.
You will work closely with stakeholders, architects, engineers, and platform teams to translate business problems into production-ready AI solutions, balancing innovation with security, governance, and measurable business outcomes.
Core Responsibilities
Design, develop, and deploy AI and Data Science solutions across multiple client engagements
Deliver Generative AI use cases, including retrieval-augmented generation (RAG), semantic search, knowledge retrieval, agentic AI workflows, and LLM-powered applications
Apply machine learning and statistical techniques to structured and unstructured data where appropriate
Evaluate, fine-tune, and optimise AI solutions for performance, reliability, cost, and business value
Translate ambiguous business requirements into clear analytical and AI use cases
Conduct exploratory analysis, feature engineering, model development, evaluation, and validation activities
Partner with Data Engineers, Architects, Product Owners, and stakeholders throughout the delivery lifecycle
Support the operationalisation of AI solutions through APIs, cloud platforms, MLOps, and downstream integration patterns
Provide technical leadership and mentoring to junior practitioners
Contribute to AI best practices, governance, responsible AI adoption, and continuous improvement initiatives
Required technical and professional expertise
Strong proficiency in Python and experience with modern Data Science and Machine Learning libraries (e.g. Pandas, NumPy, scikit-learn, PyTorch, TensorFlow)
Practical experience designing and delivering AI or Machine Learning solutions within a commercial, consulting, or enterprise environment
Hands-on experience with Generative AI technologies, including one or more of:
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Agentic AI workflows
Embeddings and Semantic Search
Prompt Engineering
AI Evaluation Frameworks * Experience working with LLM APIs and AI ecosystems such as OpenAI, Anthropic, Azure OpenAI, LangChain, LangGraph, DSPy, or similar technologies
Experience working with cloud platforms such as AWS, Azure, or GCP
Strong understanding of model evaluation, experimentation, data quality, and AI governance considerations
Excellent communication and stakeholder engagement skills, with the ability to explain complex technical concepts to non-technical audiences
Proven experience delivering solutions end-to-end, from discovery through to deployment and adoption
This role is subject to pre-employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). An additional range of Personal Security Controls referred to as National Security Vetting (NVS) may apply, this could include meeting the eligibility requirements for The Security Check (SC) or Developed Vetting (DV).
Preferred technical and professional experience
Experience deploying and operationalising AI solutions in production environments
Experience with vector databases, knowledge graphs, GraphRAG, entity resolution, recommendation systems, or semantic retrieval architectures
Experience with MLOps, model monitoring, observability, and AI platform engineering
Experience working within regulated or high-assurance environments, including Public Sector, Defence, Financial Services, or Critical National Infrastructure
Experience contributing to AI governance, responsible AI, model risk management, or security-related controls
Familiarity with SQL and modern data platforms such as Databricks, Fabric, Snowflake, Synapse, or equivalent cloud-native analytics environments
Active UK Security Clearance.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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