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Harnham

Data Scientist

London
£70k – £100k/yr
Posted about 22 hours ago
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Senior Data Scientist - Propensity modelling and Causal inference

London hybrid
Up to £100,000

This is an opportunity to join a highly established, product led organisation where data plays a central role in shaping customer strategy. The focus of the role is on moving beyond prediction into causal understanding, helping the business better quantify the real impact of customer behaviour at scale.

The Company

They are a global consumer platform with a large and highly engaged user base, operating in a digital, subscription driven environment. The business combines strong brand presence with a sophisticated data ecosystem, offering access to high quality behavioural and transactional data. Data science is well embedded, with close alignment to product and commercial teams. There is a strong emphasis on using data to inform decisions that directly impact customer experience and long term value.

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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

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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Strong

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.

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The Role

  • Work within the Customer Lifetime Value team, focusing on causal inference and incrementality
  • Apply techniques such as propensity modelling, propensity score matching and Double Machine Learning
  • Use counterfactual approaches to understand the true impact of customer actions
  • Measure incrementality across products, features and behaviours
  • Translate technical work into clear insights for non technical stakeholders
  • Partner with product and commercial teams to shape decisions
  • Support the productionisation of models and analytical solutions

Your Skills & Experience

  • Strong statistical foundation with experience in causal inference or experimentation
  • Commercial experience working with customer or product data
  • Familiarity with propensity modelling, incrementality or similar methodologies
  • Comfortable explaining technical concepts to a wider business audience
  • Experience delivering work end to end, including deployment
  • Background in sectors such as subscription, telecoms, fintech or technology is beneficial
  • A Masters degree in a quantitative discipline is preferred

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What They Offer

  • Salary up to £100,000
  • Hybrid working with a London base
  • A role with clear business impact and visibility
  • Opportunity to deepen expertise in causal inference and advanced methods
  • Supportive, collaborative team environment with regular in person time

How to Apply

If you are interested in applying data science to understand real commercial impact, please apply with your CV.

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Skills

Causal Inference
Propensity Modelling
Incrementality
Statistical Analysis
Data Science
Customer Data
Product Data
Technical Communication
Model Deployment
Analytical Solutions
Double Machine Learning
Counterfactual Approaches
Customer Lifetime Value
Experimentation
Data Ecosystem
Behavioral Data

Location

London, England, United Kingdom

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