Data Scientist I

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.

How you'll have an impact:

• Be directly responsible for the performance of enterprise merchants with household names

• Research real-time fraud patterns with our Risk Intelligence team

• Deploy fraud-fighting rules and model threshold adjustments to combat fraud in real-time

• Improve the important components of the Signifyd Commerce Protection Platform

• Communicate complex ideas to a variety of audiences, including executives

• Contribute to building production machine learning models that identify fraud

• Write production and offline analytical code in Python

• Work with distributed data pipelines

• Collaborate with engineering teams to strengthen our machine-learning pipeline

Past experience you'll need:

• A degree in a STEM related field, or equivalent work experience

• 2+ years of post-undergrad work experience required

• Experience leading projects

• Strong verbal and written communication skills

• Able to translate ambiguous problem statements into actionable analyses

• Able to influence peers through storytelling with data

• Write code and review others' in a shared codebase in Python

• Practical SQL knowledge

• Design experiments and collect 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

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Benefits in our US offices:

• Discretionary Time Off Policy (Unlimited!)

• 401K Match

• Stock Options

• Annual Performance Bonus or Commissions

• Paid Parental Leave (12 weeks)

• On-Demand Therapy for all employees & their dependents

• Dedicated learning budget through Learnerbly

• Health Insurance

• Dental Insurance

• Vision Insurance

• Flexible Spending Account (FSA)

• Short Term and Long Term Disability Insurance

• Life Insurance

• Company Social Events

• Signifyd Swag

Compensation: 

In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.

Base Salary Ranges by Pay Zone:

• Tier 1 (NYC/SF Bay Area/Seattle): $100,000 – $125,000 annually

• Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$95,000 – $120,000 annually

• Tier 3 (US - All Other): $85,000 – $110,000 annually

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.