Data Scientist

Upgrade is a fintech company that provides affordable and responsible credit, mobile banking, and payment products to everyday consumers. We were the fastest growing company in the Americas last year according to the Financial Times and Upgrade Card was the fastest growing credit card in America two years in a row. We have delivered over $33 billion in affordable and responsible credit to our 5.5M customers. The company is backed by some of the most prominent technology investors and was recently valued at $6.3B.

We have built an energizing, collaborative and inclusive culture where team members help each other, learn and innovate to move the company and its customers in the right direction, and own the outcome of their efforts.

Upgrade has been named a “Best Place to Work in the Bay Area” three years in a row, “Top Companies to work for in Arizona” and one of the "Best Engineering Department" awarded annually by Comparably. We've also received recognition for being a best company for Diversity, Women, Culture, and Veterans.

We are looking for new team members who get excited about designing and delivering new and better products to join a team of 1850 talented and dedicated professionals. Come work with us if you like to tackle big problems and make a meaningful difference in people's lives.

About the Role:

We are seeking a highly analytical and results-driven Data Scientist to join our growing analytics team in the financial services sector. You will play a key role in building predictive models, optimizing financial decisions, and extracting insights that drive product development, risk mitigation, and customer strategy. This role requires a strong foundation in statistics, machine learning, and financial domain knowledge. This position is based in our San Francisco office in a hybrid capacity (specifically on Tuesdays, Wednesdays, and Thursdays).

What You’ll Do: 

• Build and deploy statistical models and machine learning algorithms to solve business problems in areas like credit risk, fraud detection, pricing, customer segmentation, and marketing attribution.
• Validate models to identify factors that may affect model performance.
• Analyze large, structured and unstructured datasets using SQL, Python or similar tools.
• Stay up to date with the latest trends and technologies in data science and fintech, actively research new tools and techniques available for model development.
• Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies.

What We Look For:

• Advanced Degree (MS/PhD) in Data Science, Statistics, Mathematics, Computer Science, Finance, or a related quantitative discipline.
• 0-2 years of hands-on experience in a data science or analytics role, preferably in financial services. 
• Experience and/or strong interest in the latest machine learning techniques (Random Forest, Gradient Boosted Trees, etc.) strongly preferred.
• Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL.
• Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.).
• Detail oriented and strong analytical skill set.
• Proactive, driven, and ability to work in a fast paced environment.

Nice to Have:

• Experience working with cloud platforms (AWS, GCP, or Azure).
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of big data technologies like Spark or Hadoop.
• Understanding of financial services concepts such as credit scoring, portfolio risk, or customer lifetime value.

What We Offer You: 

• Competitive salary and stock option plan
• 100% paid coverage of medical, dental and vision insurance 
• Flexible PTO
• Opportunities for professional growth and development  
• Paid parental leave
• Health & wellness initiatives

The compensation range of this position in San Francisco, CA is USD $100,000-$115,000 annually plus equity and benefits. Within this range, an individual's base pay will be dependent on a variety of factors, including without limitation, job-related knowledge, skills, education, and experience.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.