Data Scientist II

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.

Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower fearless commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company valueshere !

Department : Applied Decision Science

The Applied Decision Science team drives client performance and ensures long-term stability. This involves a diverse range of responsibilities, from feature engineering and client-specific models that address unique regional or business needs, to adjusting thresholds and creating rules for optimal decisioning outcomes. We lead critical proof-of-value studies, conduct in-depth pricing analyses, and perform swift loss investigations to properly mitigate fraud attacks. We thrive on collaboration with the Risk Intelligence, Chargeback Investigation, and Product teams, and our contributions include pioneering novel modeling methods, advanced feature engineering, and robust mitigation management.

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 :

Experience we love to see :

Check out our Director of Data Science featured in Built In

Benefits in Mexico :

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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Signifyd LATAM Candidate Demographic Questions

Signifyd is an equal opportunity employer. We celebrate diversity and are fully committed to creating an inclusive, safe environment for all candidates and employees. Candidate demographic data in the aggregate provides a wealth of information that we can use to assess progress against our diversity and inclusion goals and identify areas we can do better. By answering these demographic questions, you are helping Signifyd become a more inclusive place for all of us to do our best work!

What is your gender?

Are you White, Black or African-American, American Indian or Alaskan Native, Asian, Native Hawaiian or other Pacific Islander, or some other race?

What is your highest level of school you have completed or the highest degree you have received?

Which of the following categories best describes your employment status?

Do you consider yourself to have a disability?

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