Data Science Manager at Signifyd

The Data Science team builds production machine learning models that are the core of Signifyd's product.
We help businesses of all sizes minimize their fraud exposure and grow their sales. We also improve the e-commerce shopping experience for individuals by reducing the number of folks' orders that are incorrectly declined and by making account hijacking 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 skills 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.
The Data Science and Engineering team at Signifyd have always had a strong contingent of remote folks, individual contributors and team leads. The challenges of working remotely aren't new to us and we have experienced iterative improvements to our remote culture.
How you’ll have an impact:

Owning the decisioning performance for a group of enterprise merchants with household names, executive attention, and a significant bottom line impact to Signifyd. 
Collaborating with internal stakeholders across Customer Success, Risk Intelligence, Sales and beyond. 
Leading a team of Data Scientists and helping them set goals, collaborate, and provide vision and guidance on key areas to scale
Providing mentorship to team members through feedback, coaching, and hands-on technical guidance, focusing on their long-term growth
Partnering with senior leaders including Product & Engineering to ensure data-driven decisions across the organization by applying the appropriate data science & analytics approaches where they will have a material impact
Thinking strategically to optimize the key components of the Signifyd Commerce Protection Platform
Collaborating with engineering teams to continuously strengthen our machine learning pipeline
Researching real-time emerging fraud patterns with our Risk Intelligence team
Building production machine learning models that identify fraud
Writing production and offline analytical code in Python 
Working with distributed data pipelines

Past experience you’ll need:

A degree in an analytical field
2+ years of experience in people management with experience building teams, growing talent and working across departments.
At least 4 years of post-undergrad work experience required
Strong stakeholder management skills
Experience leading projects that depend on the contributions of others in multiple teams
Using visualizations to communicate analytical results to stakeholders 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

Experience we love to see:

Experience managing remote teams
Previous work in fraud, payments, or e-commerce
Data analysis in a distributed environment
Passion for writing well-tested production-grade code

#LI-Remote
(Colorado and New York City only*) Minimum salary of $160,000 + bonus + equity + benefits. Our salaries are determined by role, level, and location. The salary minimum displayed on each job posting reflects the minimum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Benefits in our US offices:

4-day workweek
Discretionary Time Off Policy (Unlimited!)
Mental wellbeing resources
Dedicated learning budget through Learnerbly
401K Match
Stock Options
Annual Performance Bonus or Commissions
Paid Parental Leave (12 weeks)
Health Insurance
Dental Insurance
Vision Insurance
Flexible Spending Account (FSA)
Short Term and Long Term Disability Insurance
Life Insurance
Company Social Events
Signifyd Swag