Data Scientist II
United States (Remote);
The Data Science team builds production ML models and risk management tools that are the core of Signifyd's product.
We help businesses of all sizes minimize their fraud exposure and grow their sales. We improve 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 team has end-to-end ownership of our decisioning engine, from research and development to online performance and risk management.
We value collaboration and team ownership -- no one should feel they're solving a hard problem alone.
Together we help each other develop our skillsets through peer review of experiments and code, group paper study to deepen our ML and stats understanding, and frequent knowledge-sharing through live demos, write-ups, and special cross-team projects.
From the beginning of Signifyd, the R&D team has always had a strong contingent of remote folks, both individual contributors and leadership. The challenges of working remotely aren't new to us and we understand that a healthy remote work culture requires active investment.
How you'll have an impact:
- Research emerging fraud patterns in real-time with our Risk Intelligence team
- Improve the important components of the Signifyd Commerce Protection Platform
- Communicate complex ideas to a variety of audiences, including executives
- Build 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 computer science or a comparable analytical field
- 3+ years of post-undergrad work experience required
- Experience leading projects
- Strong verbal and written communication skills
- Strong machine learning and statistical background and a track record of being able to deliver under pressure.
- 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
- This role has on-call shifts, as part of our weekend rotation, Fri/Sat/Sun. While the number of shifts is subject to change, currently it works out to about six weekends a year.
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
Check out our Director of Data Science featured in Built In
Benefits in our US offices:
- 4-day workweek
- 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
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.
Signifyd provides a base salary, bonus, equity and benefits to all its employees. Our posted job may span more than one career level, and offered level and salary will be determined by the applicant’s specific experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.
USA Base Salary Pay Range$115,000—$135,000 USDTags: Computer Science Data analysis Data pipelines E-commerce Engineering Linux Machine Learning ML models PhD Pipelines Privacy Python R R&D Research SQL Statistics
Perks/benefits: 401(k) matching Career development Equity / stock options Flex hours Flexible spending account Flex vacation Health care Insurance Parental leave Salary bonus Team events Unlimited paid time off
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