Wise on cord

Wise

Lead Data Scientist

External position
London, UK
Hiring internally for Wise?
FinTech · Payments
Formerly TransferWise. Still building the world's most international account.
Active
over 6 months ago
Posted
a week ago
Checked
cord regularly checks that external positions are still open
9 hours ago

Skills & Experience

Job roles: Data Scientist
Experience level: Lead
Core skills considered: SQL, Python, Machine Learning
Other skills considered: NLP, Data Analysis

Logistics

Base salary: £90K - £130K
Employment type: Permanent
Remote working: On-site
Visa sponsorship: Not available

Job Description

We're looking for an experienced Data Scientist to join our Customer Support team in London, working as part of a team based across London and Budapest.

You'll help us understand how well our customer support experience is working, identify the biggest opportunities for improvement, and shape the path towards greater automation.

This is an analytical Data Science role with a strong product focus. You'll use customer, conversational and operational data to measure service quality, diagnose issues, propose solutions and evaluate whether they improve outcomes. A key part of the role is simplifying complex customer journeys and operational systems into clear, tractable problems the team can act on.

You'll work closely with Product, Design, Operations and Engineering to build a shared understanding of how the system works and turn insight into action.


What you'll do

Measure and diagnose

  • Build a clear, data-driven understanding of customer support quality across human and automated channels.
  • Design metrics that reflect meaningful customer outcomes, including resolution quality, customer effort, process adherence, consistency, fairness, durability of resolution and cost effectiveness.
  • Identify the root causes of issues by combining machine learning, statistical methods and domain expertise from colleagues to understand what genuinely drives customer outcomes.

Identify and test solutions

  • Turn analytical insight into concrete proposals to improve the customer experience, including product changes, process improvements, automation and better human support.
  • Quantify the potential impact and value of opportunities to help the team prioritise where to invest.
  • Design and analyse experiments to determine whether proposed changes genuinely improve customer and business outcomes.
  • Use statistical modelling and causal inference where controlled experiments are not practical.

Shape the automation strategy

  • Determine the right intervention for different customer problems - whether they should be automated, augmented by AI, handled by people or prevented altogether.
  • Test and evaluate interventions to understand their impact on customer outcomes, operational effectiveness and cost.
  • Shape the long-term automation capability roadmap, identifying what we should build next to maximise the value delivered over time.

What we're looking for

Essential

  • An ability to simplify complex systems and ambiguous problems into clear hypotheses, useful abstractions and tractable analytical questions.
  • Strong analytical judgement, with the ability to get to a useful answer quickly, refine it iteratively, and know when the evidence is sufficient to support a decision.
  • Strong SQL and Python skills, with experience working with large, complex and imperfect datasets.
  • Strong grounding in statistical analysis (e.g., classical ANOVA, non-parametric uncertainty quantification, Bayesian estimation) and causal inference, with experience designing both controlled experiments and observational studies.
  • Experience applying machine learning, statistical modelling, NLP and LLM-based techniques to analyse customer behaviour and conversational data, diagnose root causes and identify the drivers of outcomes.
  • Experience designing measurement frameworks for complex customer journeys and evaluating the impact of interventions.
  • Strong product and business judgement, with a track record of using Data Science to influence important business decisions and drive measurable impact.

Preferred

  • Experience working on customer-facing products, ideally in customer support, customer operations or another high-volume service environment.
  • Experience evaluating the impact of automation or AI-powered customer experiences.
  • Experience applying predictive or behavioural modelling to support product or operational decision-making.
  • Experience working with sensitive customer data in environments with strong security, privacy or compliance requirements.
  • Experience combining quantitative analysis with qualitative or expert insight to solve complex problems.
  • Familiarity with modern analytics and machine learning tooling in a cloud environment such as AWS.

What success looks like

Success in this role means making a complex customer support system understandable enough that the team can make better decisions about it.

You'll create clear ways of thinking about customer support quality, identify the biggest opportunities to improve outcomes, and turn those insights into concrete interventions that can be tested and measured.

Over time, you'll help us make better decisions about where to automate, where to invest in human support, and which new capabilities to build - creating a support model that delivers more value to customers while becoming increasingly effective and scalable.

Company Benefits

  • Stock Options
  • Private Pension
  • Hybrid WFH Model
  • Paid Sabbatical after 4 years
  • 90 day global remote working
  • Annual Development Budget
Lead Data Scientist at Wise
Position posted a week ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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