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As a Data Scientist within the Analytics Team
As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients. Working closely with the Data & Analytics Manager and senior colleagues, you will deliver data science projects and collaborate with stakeholders across data strategy, sales, account management, delivery, and marketing.
You will bring solid technical skills and commercial awareness to deliver data solutions that drive measurable operational performance. This is a hands-on role - ideal for someone who thrives on translating data into actionable insight and producing high-quality outcomes.
Responsibilities
- Deliver data science projects, from problem definition through to actionable insights and presentation of results
- Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes
- Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources and formats
- Translate complex analyses into clear, commercially relevant recommendations for clients and internal stakeholders
- Work with client teams to identify analytical opportunities, support marketing strategy, and quantify the impact of data-driven decision-making
- Support pre-sales and client engagement, helping to demonstrate the value of data insight
- Follow best practices in data science, reproducible research, and ethical AI
- Collaborate cross-functionally to enhance the company's products and marketing data solutions
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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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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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
What Success Looks Like in the Role


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- Delivery of impactful, high-quality analytics that directly inform and improve client marketing outcomes
- Building trust and credibility with clients as an analytical consultant
- Regular iteration on our machine learning methodologies, tools, and frameworks
- Consistent demonstration of technical excellence and commercial insight in all project deliverables
- Measurable contribution to the enhancement of Sagacity's data science and analytics product suite
Competencies and Experience
- 2+ years' experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking, or Utilities industries; or within a data-related consultancy
- Educated to degree level (postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar
- Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP)
- Proficient in Python and/or R, with strong experience in data quality, model development, and feature engineering
- Strong command of SQL and familiarity with data engineering environments such as Databricks or similar
- Skilled in data visualisation and storytelling using tools such as Power BI, Tableau, Plotly, or Sigma
- Demonstrated ability to translate technical findings into strategic recommendations for non-technical audiences
- Commercially aware, with proven success in applying analytics to solve business problems
- Strong communicator; able to engage stakeholders and present findings with clarity and confidence
- Self-motivated, organised, and proactive, with the ability to manage multiple priorities and stakeholders in a fast-paced environment
- Willing to travel across the UK for client engagements
- Must have the right to work in the UK and a commitment to ongoing professional development
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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