Solas IT Recruitment
Data Scientist - Maidenhead (£40-45k

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Data Scientist
Location: Maidenhead – Hybrid (3 days per week in the office)
Type: Permanent
Benefits: Bonus + Pension + Private Health
About the Company
An established technology-led organisation that develops data-driven solutions used by a broad customer base. Having built a very solid technical team with low staff attrition, a collaborative culture and a strong emphasis on developing people internally. The successful candidate will join a supportive Data and Engineering function where they will have exposure to interesting technical challenges, modern AI technologies and plenty of opportunity to progress their career.
The position comes with an excellent salary package, great benefits, hybrid working and very good long-term career progression.
What we are looking for
We are looking for a Data Scientist who enjoys turning complex datasets into practical insights and building analytical and machine learning solutions that solve genuine business problems.
You will work across the lifecycle of data science projects, from exploring and preparing data through to experimentation, predictive modelling, testing and implementation.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
The ideal candidate will bring:
- Commercial or academic experience applying data science, statistical or machine learning techniques to real-world problems.
- Strong programming ability using Python, with R experience considered an advantage.
- Good knowledge of SQL and relational databases.
- Experience analysing and interpreting large or complex datasets.
- Knowledge of machine learning and predictive modelling techniques.
- Experience designing experiments, testing hypotheses or carrying out A/B testing.
- Understanding of data visualisation and presenting analytical findings clearly.
- Exposure to AI-assisted development tools such as Claude Code, ideally alongside an understanding of agentic AI.
- A degree in Data Science, Statistics, Mathematics or another relevant quantitative discipline.
Responsibilities
- Exploring complex datasets to uncover patterns, trends and commercially useful insights.
- Designing, building and improving machine learning and predictive models.
- Using statistical analysis and experimentation to test ideas and measure outcomes.
- Developing data preparation processes and supporting ETL/data processing workflows.
- Working alongside Data Engineers to improve the reliability, accessibility and quality of data.
- Creating automated testing around analytical processes, data workflows and models.
- Contributing to technical discussions and helping shape the design of new solutions.
- Developing an understanding of the relevant business domain to identify new modelling opportunities and useful features.
- Communicating results and recommendations clearly to both technical stakeholders and wider business teams.


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Nice to Have
Experience in any of the following would be particularly useful:
- R
- AWS
- Cloud-based data or machine learning environments
- Claude Code or similar AI-assisted development tools
- Agentic AI / AI agents
- Building or supporting production machine learning solutions
- ETL and data engineering concepts
- Automated testing of data science or ML workflows
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