Data Scientist
At Possible, we create financial technology products that are built to benefit our customers’ economic mobility. As a Public Benefit Corporation, it’s not only our mission but our responsibility to succeed. We grow our team accordingly—through a selective process that prioritizes candidate and employee experience alike.
Job Description
Team Introduction
Our data science team sits at the center of a growing company, building the models, tools, and analytical infrastructure that power how Possible makes decisions, monitors risk, and operates with rigor at scale. We are seeking a Data Scientist to work at the intersection of analytics, model governance, and internal tooling – growing our capacity to support the teams and systems that help Possible move fast and make good decisions.
The Role
You will own a structured framework to evaluate new data sources and modeling techniques. Your analyses will include clear assumptions that guide our data vendor budget and investment decisions. You will build out model monitoring and governance infrastructure — turning it from a reactive compliance exercise into a proactive utility. Working cross-functionally, you'll collaborate with internal teams to develop analytical tools and automations that ease bottlenecks. This enables other teams to access data independently and find answers without relying on advanced analytics repeatedly.
What You'll Bring
Must-Have
- 2–4 years of hands-on experience in data science or analytics
- Strong Python and SQL skills for analysis and automation
- Proven statistical foundation: you can frame a hypothesis, develop a meticulous test, and communicate results — including their limitations — to non-technical partners
- Strong data visualization skills
- A service mentality: you build things people actually use, you get happiness from unblocking others, and you know how to balance rigor with shipping
Preferred
- Background in consumer finance or credit risk
- Experience with model governance or model validation
- Experience with AI or LLM platforms in an applied context
- Track record supporting cross-functional teams with analytical work
- Testing or QA mentality — validating that what was built does what it should
Nice-to-Have
- Experience with dbt or Airflow
- Dashboard design and management experience
This is a hybrid position with a shared in-office schedule of Monday, Tuesday, and Thursday. Our office is centrally located in downtown Seattle.
The compensation range for this role is $161,000 to $175,000. In addition to base salary, We also offer significant stock options, comprehensive benefits, a bonus plan, commuter benefits, and an excellent office space with complimentary drinks and food options.
Team Introduction
Our data science team sits at the center of a growing company, building the models, tools, and analytical infrastructure that power how Possible makes decisions, monitors risk, and operates with rigor at scale. We are seeking a Data Scientist to work at the intersection of analytics, model governance, and internal tooling – growing our capacity to support the teams and systems that help Possible move fast and make good decisions.
The Role
You will own a structured framework to evaluate new data sources and modeling techniques. Your analyses will include clear assumptions that guide our data vendor budget and investment decisions. You will build out model monitoring and governance infrastructure — turning it from a reactive compliance exercise into a proactive utility. Working cross-functionally, you'll collaborate with internal teams to develop analytical tools and automations that ease bottlenecks. This enables other teams to access data independently and find answers without relying on advanced analytics repeatedly.
What You'll Bring
Must-Have
- 2–4 years of hands-on experience in data science or analytics
- Strong Python and SQL skills for analysis and automation
- Proven statistical foundation: you can frame a hypothesis, develop a meticulous test, and communicate results — including their limitations — to non-technical partners
- Strong data visualization skills
- A service mentality: you build things people actually use, you get happiness from unblocking others, and you know how to balance rigor with shipping
Preferred
- Background in consumer finance or credit risk
- Experience with model governance or model validation
- Experience with AI or LLM platforms in an applied context
- Track record supporting cross-functional teams with analytical work
- Testing or QA mentality — validating that what was built does what it should
Nice-to-Have
- Experience with dbt or Airflow
- Dashboard design and management experience
This is a hybrid position with a shared in-office schedule of Monday, Tuesday, and Thursday. Our office is centrally located in downtown Seattle.
The compensation range for this role is $161,000 to $175,000. In addition to base salary, We also offer significant stock options, comprehensive benefits, a bonus plan, commuter benefits, and an excellent office space with complimentary drinks and food options.
