Data Scientist II - Signifyd

At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients' success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.

The Applied Decision Science (ADS) team builds production ML models and risk management tools that are the core of Signifyd's product. We help businesses of all sizes minimize their fraud exposure and grow their sales. We improve the e-commerce shopping experience for everyone by reducing the friction experienced by good buyers and blocking fraudulent purchase attempts.

ADS builds and manages the entire decision stack - from designing and deploying the ML models that assess the riskiness of a transaction, to building the tools the Risk team uses to manage and fight fraud. We seek to standardize and automate repetitive work so we can spend more time on experiments and high-leverage projects.

We value collaboration and team ownership. Data scientists in Signifyd are true “full stack” operators, requiring knowledge of how transaction information received via our API traverses its way through our system and into the models we are responsible for building. When you test a hypothesis at Signifyd, you’re responsible for the end-to-end development, deployment, and evaluation process.

Responsibilities

• Partner with the Business Unit Lead and their merchant portfolio to identify gaps in decisioning performance and implement solutions, with guidance from senior team members.
• Utilize existing, or build net new production machine learning models that identify fraud, in collaboration with other data scientists and machine learning engineers.
• Identify and build automation that reduces repetitive manual work.
• Run experiments to identify optimal decisioning strategies, balancing complexity and performance.
• Communicate complex ideas to a variety of audiences, from Customer Success and Sales, to limited interactions with external customers.
• Write production and offline analytical code in Python.
• Work with distributed data pipelines in Spark/Databricks/GCP.

Requirements

• A degree in computer science or a comparable analytical field.
• 3+ years of post-undergrad work experience required.
• Strong verbal and written communication skills.
• Strong machine learning and statistical background.
• Write code and review others' in a shared codebase in Python.
• Practical SQL knowledge.
• Design experiments and collect data.
• Experience with distributed analytics and data tooling such as Spark and Databricks.
• This role has on-call shifts, as part of our weekend rotation, Fri/Sat/Sun (currently about six weekends a year).

Nice to Have

• Previous work in fraud, payments, or e-commerce.
• Data analysis in a distributed environment.
• A passion for writing well-tested production-grade code.
• Experience with AI coding agents and automation.
• Experience of running A/B tests in production environments.
• An advanced degree.

UK Benefits

• Stock Options
• Annual Performance Bonus or Commissions
• Pension matched up to 8%
• Access to health, dental and optical insurance scheme
• Generous annual leave plus public holidays
• Cycle to Work Scheme
• Enhanced maternity and paternity leave
• Regular paid social events organized by our social committee
• Mental wellbeing resources
• Dedicated learning budget through Learnerbly