Senior Data Scientist at GoCardless | JobProMax

About Us at GoCardless

GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking.

GoCardless processes US$130bn+ of payments annually, across 30+ countries; helping customers collect and send both recurring and one-off payments, without the chasing, stress or expensive fees. We use AI-powered solutions to improve payment success and reduce fraud. And, with open banking connectivity to over 2,500 banks, we help our customers make faster, more informed decisions.

We are headquartered in the UK with offices in London and Leeds, and additional locations in Australia, France, Ireland, Latvia, Portugal and the United States.

At GoCardless, we're all about supporting you! Were committed to making our hiring process inclusive and accessible. If you need extra support or adjustments, reach out to your Talent Partner were here to help!

And remember: we dont expect you to meet every single requirement. If youre excited by this role, we encourage you to apply!

The role

Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention.

As a Senior Data Scientist within our Payment Intelligence team, youll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. Youll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network.

At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale.

What youll do

Lead the end-to-end delivery of models at scale, from initial discovery and feature engineering to production, A/B testing and continuous monitoring.
Collaborate with product and engineering peers to turn complex data into real-time, mission-critical fraud prevention solutions.
Raise the teams collective bar through hands-on technical leadership and knowledge sharing.
Proactively research and integrate latest developments in ML and payer fraud prevention to drive innovation at GoCardless.

What excites you

Being a self-starter who thrives on taking a vague business problem and owning the journey from the first prototype to a live, measurable solution.
An opportunity to introduce and scale advanced architectures to solve high-stakes fraud and payment challenges.
Moving beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job.
Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.

What excites us

You hold a degree (or PhD) in a STEM discipline or an equivalent commercial experience.
You bring hands-on experience with sophisticated architectures, such as deep learning, graph-based, or sequence-based models (experience in Fintech, Fraud Prevention, or Payments is a big plus).
You can translate complex ML concepts into practical product solutions and communicate these ideas clearly to non-technical peers.
You are comfortable owning the full lifecycle, from deep-dive analysis and feature engineering to prototyping, validation, and live A/B testing.
You lead by example, writing clean, high-quality code and raising the teams technical bar through knowledge sharing and code best practices.

Base salary range: 64,000 - 96,000

Base salary ranges are based on role, job level, location, and market data. Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work.

The Good Stuff!

Wellbeing: Dedicated support and medical cover to keep you healthy.
Work Away Scheme: Work from anywhere for up to 90 days in any 12-month period.
Hybrid Working: Our hybrid model offers flexibility, with in-office days determined by your team.
Equity: All permanently employed GeeCees get equity to share in our success.
Parental leave: Tailored leave to support your life's great adventure.
Time off: Annual holiday leave based on your location, supplemented by 3 volunteer days and 4 wellness days.

Life at GoCardless

We're an organisation defined by our values; We start with why before we begin any project, to ensure its aligned with our mission. We make it happen, working with urgency and taking personal accountability for getting things done. We act with integrity, always. We care deeply about what we do and we know it's essential that we be humble whilst we do it. Our Values form part of the GoCardless DNA, and are used to not only help us nurture and develop our culture, but to deliver impactful work that will help us to achieve our vision.

Diversity & Inclusion

Were building the payment network of the future, and to achieve our goal, we need a diverse team with a range of perspectives and experiences. As of July 2024, heres where we stand:

45% identify as women
23% identify as Black, Asian, Mixed, or Other
10% identify as LGBTQIA+
9% identify as neurodiverse
2% identify as disabled

If you want to learn more, you can read about our Employee Resource Groups and objectives here as well as our latest D&I Report

Sustainability at GoCardless

Were committed to reducing our environmental impact and leaving a sustainable world for future generations. As co-founders of the Tech Zero coalition, were working towards a climate-positive future. Check out our sustainability action plan here.

Find out more about Life at GoCardless via X, Instagram and LinkedIn.

Senior Data Scientist

GoCardless

Job Description