Data Scientist at Catch

About us:
We’re on a mission to unlock more rewarding relationships between merchants and their customers, starting with changing the way we pay for things online. Backed by Sequoia, Index Ventures, and Forerunner, as well as the founders of Affirm, Warby Parker, Allbirds, Casper, and DoorDash, Catch is a new payment service that allows both merchants & consumers to save money by cutting out credit card processing fees. Everyone wins – except the big banks!​​

We’re a fully distributed, tight-knit team of ~45 today. Building a diverse team is paramount to our success and fostering a healthy company culture, and we’re committed to an equitable interviewing process for all candidates.

The Role:
The data scientist in this role will have two core responsibilities:

Primarily, they will be responsible for end-to-end ownership of the data, analytics and machine learning that powers our fraud and risk engines. This person will join a cross-functional team of product managers, software engineers and operations managers to improve Catch’s fraud-fighting capabilities. This work will require thinking strategically, developing metrics, performing analysis, and building rules/ML models to identify would-be fraudsters.

Secondarily, this person will support the wider data science and analytics functions within Catch. As a data science leader, this person will be responsible for setting the direction and roadmap of our data science function at Catch, while supporting company-wide data science needs such as analyzing experiments, maintaining our data infrastructure, and improving our data efficiency.

What will you do?
- Work cross-functionally with product managers, software engineers and operations managers to build a comprehensive fraud-fighting product
- Analyze data, find trends and develop rules/ML models to identify would-be fraudsters
- Maintain metrics and KPIs to understand our performance in preventing fraud
- Own company-wide data science functions such as experimentation, data infra and dashboarding
- Develop data science strategy and roadmap for both fraud and company-wide data science needs
- Contribute to Catch product strategy by providing data-backed insights

What skills and experience do you need?
- 3+ years of relevant data science or fraud/risk analytics experience
- Proficiency in a scientific computing language and environment (e.g. python/pandas/jupyter, R, matlab, etc.)
- Proficiency in a querying language (e.g. SQL)
- Proficiency in data analysis, data exploration and data visualization
- Experience with ML systems - specifically classifiers
- Experience with experimentation and A/B testing
- Strong communication skills, with the ability to create data-backed arguments to influence stakeholders
- Prior experience with risk/fraud

Some additional experience is nice to have, but not necessary:
- Experience with modern data stacks and ETL/ELT systems
- Experience working within a startup environment and scaling a data science function

Catch’s Employee Benefits (not exhaustive & will grow over time):
- Comprehensive medical, dental, and vision
- Generous family leave policy— four months for either parent
- Unlimited vacation (and we encourage folks to take the time off that they need)
- Focus Fridays: No internal meetings on Fridays so you can end the week with focus time!
- A $500 Home Office Stipend to set up your work from home space
- A $500 per year Learning & Development stipend for personal & career growth
- $50 in Catch credits every month to spend at our merchants

Catch is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Research shows that while men apply to jobs when they meet an average of 60% of the criteria, women and other marginalized folks tend to only apply when they check every box. So if you think you have what it takes, but don't necessarily meet every single point on the job description, please still get in touch. We'd love to have a chat and see if you could be a great fit.

The annual salary range for the expected level for this role is $160,000- 180,000 at time of posting. Compensation also includes equity and comprehensive benefits. Final offer amounts are determined by multiple factors including candidate experience and expertise, and may vary from the amounts listed above.