Data Scientist II - Fraud & Production ML (Remote UK)

Signifyd; United States; Remote; USD 86,000 - 120,000; Full time

Benefits offered by this job

Stock Options

Annual Performance Bonus or Comissions

Pension matched up to 8%

Day one health, dental and optical

Generous annual leave

Cycle to Work Scheme

Enhanced parental leave

Social events

Mental wellbeing resources

Learning budget

Job summary

Signifyd is hiring a data scientist for its Applied Decision Science team. You will build production ML models to assess fraud risk, automate repetitive tasks, and run experiments that improve decisioning while collaborating with data engineers and stakeholders.

We value end-to-end ownership, peer reviews, and the ability to translate complex results for non-technical audiences. This role supports remote work with flexible teams across regions.

Qualifications

• 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 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, Fri/Sat/Sun weekends (about six weekends per year).

Responsibilities

• Partner with the Business Unit Lead to identify gaps in decisioning performance and implement solutions.
• Build and deploy production ML models to identify fraud.
• Identify and automate repetitive manual work.
• Run experiments to optimize decisioning strategies.
• Communicate complex ideas to various audiences.
• Write production and offline analytical Python code.
• Work with distributed data pipelines in Spark/Databricks/GCP.

Skills

Communication

Machine Learning

Python

SQL

Experiment Design

Distributed Analytics

Education

Bachelor's degree in CS or related field

Tools

Spark

Databricks

Job description

Signifyd is hiring a data scientist for its Applied Decision Science team. You will build production ML models to assess fraud risk, automate repetitive tasks, and run experiments that improve decisioning while collaborating with data engineers and stakeholders.

We value end-to-end ownership, peer reviews, and the ability to translate complex results for non-technical audiences. This role supports remote work with flexible teams across regions.