Senior Data Scientist, Fraud ML (Remote)

CrossTalent; United Kingdom; Remote; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Stock Options

Annual Bonus/Commissions

Pension matched up to 8%

Health, dental & optical insurance

Generous annual leave & publicholidays

Cycle to Work Scheme

Learning budget

Job summary

Signifyd is seeking a data scientist to join the Applied Decision Science (ADS) team. You will design, deploy, and evaluate ML models that assess transaction risk and reduce fraud, collaborating with data scientists and ML engineers.

Expect to work with distributed data pipelines and production-grade Python code. Remote UK role with weekend on-call shifts, a collaborative culture, and a strong benefits package.

Qualifications

• Degree in computer science or comparable analytical field.
• 3+ years of post-undergrad work experience.
• Strong ML and statistical background with Python coding ability.
• Proficiency in SQL and distributed data tooling (Spark/Databricks).
• Excellent written and verbal communication skills.

Responsibilities

• Identify gaps in decisioning performance and implement solutions.
• Build production ML models to identify fraud in collaboration with data scientists and ML engineers.
• Design experiments and collect data to optimize decisioning strategies.
• Write production and offline analytical code in Python.
• Work with distributed data pipelines in Spark/Databricks/GCP.
• Balance model complexity and performance while reducing manual work.

Skills

Python

SQL

Spark

Databricks

Machine learning

Experiment design

Communication

Education

Bachelor's degree in computer science or related field

Tools

Python

Spark

Databricks

Job description

Signifyd is seeking a data scientist to join the Applied Decision Science (ADS) team. You will design, deploy, and evaluate ML models that assess transaction risk and reduce fraud, collaborating with data scientists and ML engineers.

Expect to work with distributed data pipelines and production-grade Python code. Remote UK role with weekend on-call shifts, a collaborative culture, and a strong benefits package.