At a Glance
- Tasks: Lead the design and delivery of AI solutions for impactful public sector projects.
- Company: Join IBM Consulting UK FutureNow, a leader in hybrid cloud and AI.
- Benefits: Flexible working, 25 days holiday, private medical cover, and continuous learning support.
- Other info: Inclusive environment that values curiosity and unique perspectives.
- Why this job: Make a real difference with cutting-edge technology while growing your career.
- Qualifications: Proficient in Python, machine learning, and data science libraries.
The predicted salary is between 63000 - 77000 £ per year.
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. 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.
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.
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.
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, colour, 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.
Data Scientist - AI & Advanced Analytics (Public Sector) employer: IBM
IBM is an exceptional employer for a Senior AI Data Scientist, offering a dynamic work environment that fosters innovation and collaboration. With a strong emphasis on mentorship and professional growth, employees are encouraged to develop their skills while working on impactful AI projects that serve both public and private sectors. The flexible hybrid work model in the UK further enhances work-life balance, making IBM a desirable place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - AI & Advanced Analytics (Public Sector)
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We think you need these skills to ace Data Scientist - AI & Advanced Analytics (Public Sector)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at IBM, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at IBM. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at IBM
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at IBM!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.