Remote Data Scientist II — Fraud & ML for E‑commerce

Coinscapture; United Kingdom; Remote; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Stock options

Annual bonus/commissions

Pension matched 8%

Health, dental & optical cover (Day 1)

Generous annual leave

Job summary

Signifyd is seeking a Data Scientist for a remote role in the United Kingdom to join the ADS team. You will build and deploy production ML models that assess transaction risk, and collaborate with data scientists and ML engineers to expand fraud-fighting capabilities.

You will run experiments, design robust experiments, and communicate results to stakeholders across Success and Sales while working with Spark, Databricks, and GCP in a distributed data environment.

Qualifications

• Degree in computer science or a comparable analytical field.
• 3+ years of post-undergrad work experience.
• Strong verbal and written communication skills.
• Strong machine learning and statistical background.
• Proficient Python coding and code review in a shared repo.
• Practical SQL knowledge.
• Design experiments and collect data.
• Experience with Spark and Databricks.

Responsibilities

• Partner with the BU Lead to identify gaps in decisioning performance and implement solutions.
• Build production ML models to identify fraud in collaboration with data scientists and ML engineers.
• Identify and build automation to reduce repetitive manual work.
• Run experiments to balance complexity and performance of decisioning strategies.
• Communicate complex ideas to audiences from Customer Success to Sales.
• Write production and offline analytical code in Python.
• Work with distributed data pipelines in Spark/Databricks/GCP.

Skills

Python

SQL

Machine learning

Communication

Distributed computing

On-call experience

Education

Bachelor's degree in CS or analytical field

Tools

Spark

Databricks

GCP

Job description

Signifyd is seeking a Data Scientist for a remote role in the United Kingdom to join the ADS team. You will build and deploy production ML models that assess transaction risk, and collaborate with data scientists and ML engineers to expand fraud-fighting capabilities.

You will run experiments, design robust experiments, and communicate results to stakeholders across Success and Sales while working with Spark, Databricks, and GCP in a distributed data environment.