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Murphy AI

Data Scientist

London
Posted about 12 hours ago
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Murphy AI

Murphy AI deploys voice AI agents that help banks collect debt. We’ve built a fully-fledged platform designed to optimize recovery rates while maintaining respectful and personalized communication. Our advanced automation streamlines the process of collecting overdue invoices for banks and other industries, providing a seamless and effective solution.

Our AI-powered agents adapt instantly, engaging with debtors across channels like voice, messengers, email, and SMS to maximize results while preserving trust. By combining advanced artificial intelligence with powerful automation, we’re setting a new standard for how businesses recover payments.

As a fast-growing startup that has already made an impact within less than a year in the market, we are building a talented team to scale our operations and drive our vision forward 🌟

About the Role

We're looking for a Data Scientist to build the Murphy’s brain — the ML that decides who we contact, when, how, and how often, to recover the most debt inside hard legal limits. Recovery is a data problem before it's a voice problem, and you own the data problem. This is one of the highest-leverage seats in the company: your models set the strategy every AI agent executes, on every call.

Murphy builds AI voice agents that collect overdue debt for banks: more recovered, faster, cheaper, fully compliant, and respectful to the debtor. We're live with Santander, Revolut, BBVA, and dozens of others. We've proven the product in large-scale pilots with top-tier banks — now we're making every contact smarter, and we need a scientist to own the models that decide how we collect.

What you'll do

  • Own the contact strategy. Who Murphy contacts, when, how often, on which channel — voice, WhatsApp, etc. — to maximise recovery inside hard legal guardrails.
  • Model the debtor. Propensity and uplift models — who picks up, who pays, who responds to which voice, script or offer — turned into live segments the agents act on.
  • Optimise with experiments. A/B tests and bandits over timing, cadence, voice and negotiation policy; find what lifts recovery, and ship it fast.
  • Own business-level outcomes. Collaborate with product, engineering, and commercial teams to define solutions and improve the key metrics.

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.

Start with a chat, not a search bar

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.

P

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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It searches the market for you

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.

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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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Strong

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.

Who you are

  • You hold a degree in mathematics, statistics, machine learning, or computer science.
  • Rigorous with probability and statistics. Experimental design, causal inference. You reach for the right tool, and you know when a result is real.
  • AI-native, ruthless on quality. You reach for AI to automate and streamline by default — and you know exactly where it gets sloppy. You never let that through, and you control quality rigorously.
  • You don’t need a collections or fintech background. We’d rather teach the domain to a killer than hire a lifer who can’t ship — you’ll pick up the domain, the data, and the regulation cold, fast.

Requirements

  • 3+ years shipping ML that ran in production and moved a business metric. Models that pick the best next action and measure whether it actually changed the outcome; ranking, pricing, or contact-strategy models. Models that ship as code, not notebooks.
  • Expert Python. Comfortable in a real production codebase (ours is Python for ML/AI services and TypeScript around it, on AWS and PostgreSQL) — you take a model from idea to production and monitor it.
  • Statistics you can defend: experimental design, causal inference, measuring the real effect of an action — not just correlations. You know when a result is real, when it’s noise, and how to test it.
  • Experimentation: you’ve designed, run, and interpreted A/B tests or bandits on live traffic, and shipped the winner.
  • You turn models into decisions: you can explain to stakeholders why the model says to call this client at 6pm — and defend it.

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🤝 What we offer

  • 💰 Salary at the top of the benchmark.
  • 📈 Fair equity with enormous upside potential.
  • 🧩 Real Ownership - Murphy's strategy is yours to drive.
  • 🙌 Small team, high autonomy, and outsized impact.
  • 🗣️ The founding team's direct attention, and a category with a $300B+ industry behind it.
  • 🛜 Hybrid & Flexible: Our default setup is hybrid – 3 days a week at our office and 2 days of remote work.

📚 Our Process

  1. First Interview – Getting to Know You

    • A conversation with a future teammate who’s excited to find a new colleague. We’ll talk about your story, what drives you, and what you’re looking for next—no trick questions, just a genuine exchange.
  2. Second Interview – Deep Dive

    • You’ll meet the Hiring Manager and potentially another team member. This is a more technical discussion where we explore your skills in detail, walk through real scenarios, and answer any questions you might have about the role.
  3. Tech Assessment or Business Case

    • A practical exercise to see how you approach challenges similar to those you’d tackle at Murphy. You’ll have time to reflect and showcase your thinking—no rush, no surprises.
  4. Call with the Founders

    • Our founders meet every team member and it’s a great opportunity for you to learn about the company and its direction.

👉 To learn more about how we hire and what to expect at every step, feel free to explore our Hiring Guide!

👉 We are committed to building a diverse, inclusive, and equitable workplace where everyone, regardless of background, identity, or experience, feels valued and empowered to thrive. We believe that different perspectives drive innovation and success, and we actively foster an environment where all voices are heard and respected.

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Jessica, London

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Skills

Python
Machine Learning
Statistics
Experimental Design
Causal Inference
A/B Testing
Bandit Algorithms
Data Modeling
Propensity Modeling
Uplift Modeling
AWS
PostgreSQL
TypeScript
Production Engineering
Data Analysis

Location

London, England, United Kingdom

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