Checkout.com on cord

Checkout.com

Director, Data Science

External position
London, UK
Hiring internally for Checkout.com?
FinTech · Payments
Our mission is to enable businesses and their communities to thrive in the digital economy.
Active
over 6 months ago
Posted
6 days ago
Checked
cord regularly checks that external positions are still open
15 hours ago

Skills & Experience

Job roles: Head of Data
Experience level: Lead, Leadership
Core skills considered: Machine Learning, Data Modeling, Data Pipelines, Data Analysis, Agile
Other skills considered: Scrum, Python, Data Protection, Data Security

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: On-site
Visa sponsorship: Not available

Job Description

Checkout.com helps businesses thrive in the digital economy by making payments work better. Within Payment Performance, Data Science is central to how we improve acceptance, reduce payment costs and protect merchants and Checkout from fraud.

We are looking for a Data Science leader to bring our Fraud and Acceptance Data Science teams together behind one strategy and way of working. The teams already exist and are building important products. Your job is to help them work as one organization, raise the bar for how models are developed and operated, and turn more of their work into measurable production impact.

You will lead a distributed group of Data Scientists working on real-time decisioning at global payments scale. The problems range from fraud detection and adaptive risk strategies to authorization optimization, routing and recovery. The common thread is using machine learning to make better decisions on every payment.

This is a player-coach role. You will set direction and develop the organization, but remain close enough to the work to challenge technical choices, lead design reviews and contribute directly when the problem calls for it.


What you'll do

  • Create one Data Science strategy across fraud and payment optimization, connected to the wider Payment Performance vision.
  • Decide where we should invest across models, data, experimentation and shared capabilities to create the greatest business impact.
  • Build common technical standards and ways of working without forcing different problem domains into the same approach.
  • Identify where new scientific methods or data assets could create a lasting competitive advantage.
  • Own the end-to-end model lifecycle, from problem framing and experimentation through evaluation, launch and production performance.
  • Improve measurable outcomes across fraud, acceptance and payment cost, with models that operate safely and reliably at scale.
  • Ensure teams optimize for business and merchant outcomes rather than research output or offline model metrics alone.
  • Raise the standard for experimentation, explainability, monitoring, drift detection and model iteration.
  • Work with Engineering to make productionization a shared responsibility: Data Science owns model performance, while Engineering owns platform reliability and deployment infrastructure.
  • Jointly prioritize the roadmap with the Fraud and Intelligent Acceptance Group Product Managers.
  • Ensure Product owns merchant problems, desired outcomes and commercial trade-offs, while Data Science owns scientific direction, model quality and technical standards.
  • Translate complex scientific choices into clear product, customer and investment decisions.
  • Partner with Engineering leaders on the architecture and capabilities needed for low-latency, resilient ML systems.
  • Spend time with merchants when direct technical engagement can uncover a better problem, build confidence or demonstrate value.
  • Lead, coach and develop Data Scientists across Fraud and Acceptance, initially managing much of the team directly.
  • Create clear ownership, goals and development paths across a distributed organization.
  • Develop future domain leads who can take on more day-to-day technical and people leadership as the teams grow.
  • Hire exceptional scientists and build a culture that combines scientific rigor, pace, curiosity and accountability.
  • Create an environment where senior scientists can challenge assumptions, do their best work and connect it to outcomes that matter.
  • Act as a technical sounding board for senior scientists across modelling, experimentation and ML-system design.
  • Lead or contribute to design reviews, prototypes and selected analyses where your involvement can materially improve the outcome.
  • Challenge teams to choose practical methods that fit the business problem, rather than defaulting to the most complex approach.
  • Keep the organization current on developments in applied AI and machine learning, and translate relevant advances into production opportunities.

What success looks like

  • United the Fraud and Acceptance teams behind one Data Science strategy and operating model.
  • Improved the production impact of models across fraud, acceptance and cost optimization.
  • Established clear decision rights and an effective joint roadmap with Product and Engineering.
  • Raised standards for model development, productionization, monitoring and measurement.
  • Created stronger consistency across the teams while preserving the expertise each domain requires.
  • Developed future technical and people leaders who can support the organization as it grows.

What we're looking for


Essential

  • A strong record of leading Data Scientists who build real-time or high-scale machine-learning products.
  • Deep technical judgment across applied machine learning, experimentation, model evaluation and production ML systems.
  • Experience taking models beyond notebooks and offline metrics into reliable products with measurable business impact.
  • The ability to coach scientists at different levels and challenge senior technical contributors with credibility.
  • Proven success leading distributed teams through change, ambiguity and growth.
  • Strong product judgment: you can connect scientific work to customer problems, commercial trade-offs and company strategy.
  • The confidence to influence senior leaders, challenge priorities and explain complex technical ideas in simple language.
  • A practical, curious mindset and a bias toward shipping, learning and improving.

We care more about the scale and impact of the systems and teams you have led than a fixed number of years in a particular title.


Valuable, but not required

  • Experience in payment fraud, authorization optimization, routing, recommendations or another real-time decisioning domain.
  • Knowledge of highly imbalanced classification, anomaly detection, graph methods, reinforcement learning or adaptive optimization.
  • Experience building low-latency models in regulated or financially sensitive environments.
  • Familiarity with causal inference, online experimentation and measuring incremental model impact.
  • Experience developing first-line managers or technical leads within a growing Data Science organization.

Company Benefits

  • Competitive Salary & Performance Bonus
  • Cutting Edge Technology & Latest IT tools
  • Company retreat (surprise annual trips)
  • Flexible working, 24 days of paid leave and Birthday off
  • Season Ticket Loan, Cycle to Work Scheme, comprehensive benefit plans
  • Internal community groups and cultural events
  • Employee-led community outreach, payroll giving and a volunteering day
  • A global wellness programme and private health insurance
  • Tailored career development and learning pathways
  • Peer recognition program and quarterly Hero Awards
Director, Data Science at Checkout.com
Position posted 6 days 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
Alex Yeates on cord
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