Staff Data Scientist, Hungary

Signifyd helps businesses of all sizes minimize their fraud exposure and grow their sales. Signifyd improves the e-commerce shopping experience for everyone by reducing the number of false positive declines of good buyers and by making fraud less profitable for criminals.

The Data Science organization at Signifyd is responsible for building, maintaining, and monitoring production ML models and risk management tools that are the core of Signifyd's product. The Senior Analyst will be part of the Merchant Solutions team within the Data Science organization. The Merchant Solutions team maintains a balance between custom and scalable solutions for Signifyd’s customers, and the Senior Analyst will be a direct influencer on how to balance the team’s approach of custom vs scalable solution development. In addition to influencing the team’s approach, the Senior Analyst will also help ensure solutions are achieving their desired results and make recommendations to adjust approaches as needed.

In terms of culture, we value collaboration and team ownership -- no one should feel they're solving a hard problem alone. Working across job functions, team boundaries, and hierarchies is not only encouraged but is required to be successful at Signifyd. We’re all in the same boat, and value team members that both seek to influence the direction of travel, and actively contribute to helping Signifyd improve the e-commerce shopping experience. 

How you'll have an impact:

• Build production machine learning models that identify fraud
• Collaborate with engineering teams to strengthen our machine learning platform
• Own and ship multiple large products, complex libraries or major pieces of software
• Deepen our understanding of the key entities used in our decisions
• Write production and offline analytics code in Python
• Communicate complex ideas to a variety of audiences
• Lead a wide range of complex situations across multiple axes: scale, uncertainty, and  interconnectedness

Past experience you'll need:

• A degree in computer science or a comparable analytical field
• 6+ years of post-undergrad work experience required
• Building production ML models
• Using visualizations to communicate analytical results to members outside your team
• Hands-on statistical analysis with a solid fundamental understanding
• Writing code and reviewing others' in a shared codebase, preferably in Python
• Practical SQL knowledge
• Designing experiments and collecting data
• Familiarity with the Linux command line

Bonus points if you have:

• Previous work in fraud, payments, or e-commerce
• Data analysis in a distributed environment
• Passion for writing well-tested production-grade code
• A Master's Degree or PhD

Check out how Data Science is powering the new era of Ecommerce