Data Scientist Ii

The Data Science team at Signifyd builds the models that power our fraud detection engine.

Our machine learning pipeline keeps us one step ahead of fraudsters and their constantly evolving tactics and our research and experiments develop into new products that improve the merchant payments experience.

We expect our data scientists to be hands-on.

We carry solutions from a brainstorm to experimentation and all the way to deployment.

We're a varied group with a diversity of strengths some team members came to us from academic backgrounds, others from engineering, some from big companies and some from small, but all of us are curious and collaborative.

We are looking for someone who embodies our

company values

Curious and Hungry :

Be willing to do research and design experiments by being hands-on

Tenacious :

Creating something new is hard work, and our Data Scientist team never gives up

Customer Passion :

Be the backbone to our platform, and help us stay ahead of fraudsters

Design for Scale :

Work with the rest of the Data Science team to make fraud protection at scale possible

Agile :

Some days you may spend doing research and designing experiments while others are spent using your analytical toolbox to surface insights into real-time fraud attacks.

Roll Up Your Sleeves :

Partner closely internally to learn from others, and succeed as a team

How you'll have an impact :

Building production machine learning models that identify fraud

Designing new algorithms that optimize all the key components of the Signifyd Commerce Protection Platform

Writing production and offline analytical code in Python and Java

Researching real-time emerging fraud patterns with the Risk Analysis team

Working with distributed data pipelines

Communicating complex ideas effectively to a variety of audiences

Collaborating with engineering teams to continuously strengthen our machine learning pipeline

Mentoring other members of the team

Past experience you'll need :

Bachelor's degree in computer science, applied mathematics, economics, or an analytical field

An advanced degree (M.S. or Ph.D) in an analytical field is a plus

At least 3+ years of experience

Hands-on statistical analysis with a solid fundamental understanding

Designing experiments and collecting data

Writing code and reviewing others' in a shared codebase, preferably in Python and Java

Practical SQL knowledge

Familiarity with the Linux command line

Fluent in English

Experience we love to see :

Data analysis in a distributed environment

Passion for writing well-tested production-grade code

Using visualizations to communicate analytical results to stakeholders outside your team

Working directly with Go-to-Market teams

Previous work in fraud, payments, or e-commerce

Check out how

Data Science is powering the new era of Ecommerce

Check out our Director of Data Science featured in

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We want to provide an inclusive interview experience for all, including people with disabilities.

We are happy to provide reasonable accommodations to candidates in need of individualized support during the

hiring

process.

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