IBM
Data Scientist - AI & Advanced Analytics
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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 Senior Data Scientist, you will play a leading role in the design and delivery of advanced data science and artificial intelligence solutions across a range of client engagements. You will work on complex, real world data problems across public sector and financial services clients, applying statistical, machine learning, and AI techniques to drive measurable outcomes.
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AI and machine learning will form a significant element of your work, alongside broader advanced analytics, decision science, and data driven insight generation.
Core Responsibilities
- Lead the design, development, and deployment of data science and AI solutions across multiple client projects
- Apply statistical modelling, machine learning, and advanced analytics techniques to structured and unstructured data
- Deliver AI enabled solutions, including exposure to foundation models, large language models, or other applied AI approaches where appropriate
- Translate ambiguous business problems into well defined analytical use cases and solution designs
- Conduct exploratory data analysis, feature engineering, model development, validation, and evaluation
- Work closely with data engineers, platform teams, architects, and stakeholders throughout the delivery lifecycle
- Provide technical leadership and mentoring to junior data scientists, contributing to team capability building and best practice
- Support technical decision making, including trade offs around accuracy, interpretability, scalability, cost, and operational risk
Preferred Education
- Bachelor's Degree
Required Technical And Professional Expertise
- Strong proficiency in Python and experience with data science and machine learning libraries (e.g. NumPy, Pandas, scikit learn)
- Practical experience applying machine learning or advanced analytics in a professional delivery environment
- Exposure to AI frameworks or techniques (e.g. TensorFlow, PyTorch, LLM APIs, or similar)
- Experience working with cloud platforms such as AWS, Azure, or GCP
- Solid understanding of data modelling, data quality, and analytical best practices
- Strong communication and problem solving skills, with the ability to explain complex concepts to non technical stakeholders
- Proven experience delivering data driven solutions end to end in a commercial or consulting context
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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 delivering AI or machine learning use cases, including NLP, forecasting, classification, optimisation, or generative AI
- Familiarity with deploying or operationalising models (e.g. model APIs, batch scoring, or integration into downstream systems)
- Experience working in regulated or high assurance environments (e.g. public sector or financial services)
- Knowledge of SQL and modern data platforms or analytics tooling
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