Product Data Scientist, New Products (Capital)
- San Francisco, CA
- Employees can work remotely
- Current Square Employee?: Apply via go/jobs with your Square email.
We are looking for experienced Data Scientists to join Square's growing Capital organization. We have an incredible team that is working to make financing easier, fair and more transparent for all businesses. As a Data Scientist on the Capital Team, you will leverage analytics, engineering, and machine learning to empower data-driven decision making in the full lifecycle of product development. Capital is expanding it's product set to help sellers meet their varying financing needs. You would partner with the various teams to drive this initiative. You will work closely with product managers and machine learning engineers. You will leverage data to predict credit and fraud risk, improve strategic decisions, and lead experimentation/growth projects.
This role will be embedded within a product team.
- Partner with multiple team members to make data-driven decisions across the organization by leveraging descriptive and predictive analytics to produce material impact
- Provide comprehensive analytics support to partner teams, primarily through development of self-serve tools (such as ETLs and Looker)
- Determine and monitor essential metrics for product projects
- Own, coordinate, and solve complex, cross-functional problems that extend beyond the traditional boundaries of product domains, analytics, and data science
- Communicate analysis and decisions to high-level stakeholders and executives in verbal, visual, and written media
- Apply a diverse set of techniques including statistics, quantitative reasoning to help grow the business
- 3+ years of analytics experience or equivalent
- Fluent in data tools for analysis and visualization (SQL, dashboards, Python/R)
- Strong problem solving skills and ability to translate ambiguous, unstructured problems into actionable data-driven analyses
- Skilled verbal and written communication to explain technical analysis to non-technical partners
- Familiarity with data warehouse design, development and best practices
- Proven ability to lead projects that depend on the contributions of others in multiple disciplines
- Experience in applying both data-backed heuristics and machine-learning techniques to solve practical product problems such as funnel optimization. Bonus points for experience applying these techniques to underwriting.
- Some background in lending, finance or risk is helpful but can be learned on the job
At Square, we want you to be well and thrive. Our global benefits package includes:
- Healthcare coverage
- Retirement Plans
- Employee Stock Purchase Program
- Wellness perks
- Paid parental leave
- Paid time off
- Learning and Development resources