Harnham
Data Scientist

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Data Scientist
London (2 days per week)
Up to £65,000
This is an opportunity to join a leading data and analytics consultancy working on a wide variety of predictive modelling projects across utilities, telecommunications, financial services, and customer insight. You'll have the chance to take ownership of projects, work directly with stakeholders, and apply Data Science techniques to solve real commercial challenges.
The Company
They are a well-established data and analytics consultancy that combines proprietary data assets with advanced analytical expertise to help organisations make better decisions. Their work focuses on customer intelligence, predictive modelling, and analytics solutions that deliver measurable business outcomes.
Working across multiple industries, they partner with clients to solve challenges around customer acquisition, retention, collections, marketing effectiveness, and operational performance. Their teams combine industry expertise, analytics, and modern data platforms to deliver impactful 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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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 Role
As a Data Scientist, you will develop predictive models and analytical solutions that support client decision-making and customer strategy.
Responsibilities include:
- Building machine learning models across use cases including propensity to pay, customer acquisition, churn prediction, lifetime value, and segmentation
- Developing classification, regression, and clustering models using customer and transactional data
- Working closely with clients and stakeholders to understand business problems and define analytical approaches
- Leading data discovery sessions and gathering requirements from subject matter experts
- Presenting insights, recommendations, and model outputs to both technical and non-technical audiences
- Monitoring, refining, and retraining models to ensure ongoing performance
- Collaborating with analysts, project managers, and industry specialists to deliver client projects
- Contributing to reports, dashboards, and client presentations
Your Skills & Experience


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- Strong commercial Data Science experience within predictive modelling
- Advanced Python and SQL skills
- Experience building classification, regression, and clustering models from the ground up
- Strong understanding of model performance, validation, and optimisation
- Confident communicating insights to technical and non-technical stakeholders
- Experience with modern cloud and data platforms such as Databricks, AWS, Azure, or Snowflake
- Exposure to customer analytics, credit risk, collections, telecommunications, or utilities is advantageous
- Comfortable taking ownership of projects and working independently
What They Offer
- Salary up to £65,000
- Hybrid working with two days per week in London
- Exposure to a broad range of Data Science and machine learning projects
- Direct client engagement and stakeholder exposure
- Access to modern cloud and analytics technologies
- Strong opportunities for technical and professional development
- Collaborative and supportive working environment
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