Possible is a venture-backed consumer fintech company that radically reinvented small-dollar loans to make them more affordable and sustainable to help everyone improve their financial health. Building on that success, Possible is adding two additional product categories in our pursuit of making financial services more fair and affordable.

Do you desire to work with large amounts of data? Are you interested in building a data science function while doing meaningful work? Have you always wanted your work to have a positive societal mission to help underserved communities?

As a Senior Data Scientist at Possible, you will work on interesting, high-impact, and intellectually stimulating data science projects. Key responsibilities including; Life cycle credit policy management ranging from acquisition to collections, underwriting/machine learning models development, credit risk portfolio reporting, and monitoring, fraud management and prevention, new product analysis and definition, campaign management, and credit strategy testing.

This role requires a high level of analytical problem solving and collaboration as you work cross-functionally to answer key strategic questions and drive decision-making. This role reports directly to the Head of Data Science and ML.

Roles & Responsibilities:

- Data Analytics

- Designing, developing and implementing machine learning models/algorithms

- Builds underwriting models to increase loan funding rates while lowering losses

- Drives improvements in customer acquisition and fund recovery

- Identifies and evaluates new data sources to improve customer acquisition and fund recovery

- Works holistically across the entire risk management continuum including marketing channel evaluation and pre-approval criteria for existing customers

- Continue to test new strategies and models and work with the fund recovery team to improve cash collection

- Drives analysis and ongoing improvements to loss performance of new markets.

- Working with other departments (including marketing, loan operations, finance, etc) evaluates new product opportunities and forecasts likely loss performance.

- Evolves strategies and pricing recommendations to improve performance as the new products scale.

Work experience and education, knowledge and skills:

• A bachelor's degree in statistics, data science, applied mathematics, computer science, or engineering is required. An advanced degree from a respected academic institution is preferred.
• 2-3 years of hands-on experience using tools such as R, Python, SQL, Spark
• Prior experience using reporting tools such as Tableau, Looker, or equivalent
• Self-starter with the ability to develop insightful financial models and quantitative analysis, paired with strong critical thinking and sound business judgment
• Excellent organizational skills with the ability to set priorities and to work simultaneously on several projects.
• Excellent analytical and numerate skills. Attention to detail.
• Experience in analyzing large scale data in both structured and unstructured settings
• Knowledge of cloud computing and AWS services is a plus

We are a fast-growing, fully distributed, fintech startup that believes financial health is something everyone deserves, not just the affluent. We're committed to empowering the underserved with tools to better their economic situation. We promise to be transparent, serve with kindness, be responsible, and hold ourselves accountable for creating positive change. Possible is backed by leading investors such as Union Square Ventures, Canvas Ventures, and FJ Labs.

Possible is fully distributed and has team members across the US and in Asia and Latin America. Our primary coordination hours are 9a to 3p Pacific Time.

Joining an early-stage, venture-backed company does not mean you will sacrifice on benefits. We offer excellent medical, dental, and vision coverage and pay 85% of employee premiums and 50% of eligible dependent premiums. We also offer childcare and healthcare FSAs; life and disability (short- and long-term) insurance; an Employee Assistant Program; and a 401(k) plan.