Senior Data Scientist - Flex Pay

Upgrade helps customers move in the right direction with affordable and responsible financial products. Since 2017, we’ve helped over 7.5 million customers access over $42 billion in consumer credit. With a relentless focus on improving our customers' financial well-being, we build products that put more money in their pocket and support their journey toward a better financial future. We’re backed by some of the most prominent technology investors and were most recently valued at $7.3B.

We’re consistently recognized for our collaborative and inclusive culture. Most recently, we were named one of the World’s Top Fintech Companies by CNBC, Best Places to Work by Built In, Best Places to Work by the San Francisco Business Times, America’s Greatest Workplaces by Newsweek, Best Startup Employer by Forbes, and Healthiest Employers by Phoenix Business Journal. 

We’re looking for new team members who get excited about designing and delivering new and better products. Come join us and help build a better financial future for millions of people.

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About the Role:

We are seeking a highly analytical and results-driven Data Scientist to join our buy now pay later (BNPL) sector called Flex Pay. You will play a key role in building predictive risk models, optimizing offers and pricing, and extracting insights that drive product development, risk mitigation, and customer strategy. This role requires a strong foundation in statistics, machine learning, and programming. 

While this position is ideally based in our San Francisco office on a hybrid basis, we are also open to considering remote candidates.

What You’ll Do: 

• Build and maintain credit and fraud policy simulators used to ensure properly functioning systems and identify risk decisioning enhancements. 
• 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.
• 3-5+ years of hands-on experience in a data science or analytics role, preferably in financial services. 
• Experience and/or strong interest in 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.).
• Proactive, driven, and ability to work in a fast paced environment.

Nice to Have:

• Experience with data visualization tools (e.g., Tableau, Power BI).
• Experience with AI tools such as Claude
• Experience with data technologies like PySpark.
• 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
• Paid coverage of medical, dental and vision insurance 
• Competitive 401(k) and RRSP program  
• 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-$150,000 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.

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Environmental & Working Conditions

Work is performed indoors in a fast-paced environment that requires the ability to manage multiple priorities and meet established workflows, schedules, and service expectations.

Employees regularly input, retrieve, and exchange information accurately using digital systems and applications to support operational and customer service objectives.

The role requires the ability to receive and exchange information with customers, peers, supervisors, and cross-functional partners through available communication channels, which may include meetings, email, phone, and digital collaboration tools, and may involve real-time, verbal, or in-person exchanges depending on business need.

Job duties may involve managing a high volume of inbound and/or outbound customer interactions and work activities using telecommunications and computer systems. The role requires the ability to read, analyze, and interpret information displayed on computer screens and remain in a working posture for extended periods, consistent with the demands of the position.

Work may be performed in a contact center, office, or remote environment, depending on business needs and the nature of the role. Onsite work environments may include shared workspaces, standard office lighting, and moderate background noise typical of customer service or operational settings.

Employees working remotely are responsible for maintaining a secure and productive workspace with reliable internet connectivity that supports company systems and safeguards the confidentiality of company and customer information.

Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of the position in accordance with the Americans with Disabilities Act (ADA) and applicable state and local laws.

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.

Upgrade does not accept unsolicited resumes from staffing agencies, search firms, or any third parties. Any resume submitted to any employee of Upgrade without a prior written agreement in place will be considered the property of Upgrade, and Upgrade will not be obligated to pay any referral or placement fee. Agencies must obtain advance written approval from Upgrade's Talent Acquisition department to submit resumes and only in conjunction with a valid, fully executed agreement.