Staff Data Scientist

EMPOWER OVERVIEW

Empower is shaking up an outdated financial system by providing real opportunity for our customers: the opportunity to get the cash they need, to access fair credit, and to change their financial story. Today, we’re helping millions of people find financial security through machine learning models that evaluate creditworthiness using a more inclusive lens and mobile-first products: Cash Advance, Thrive line of credit, and Petal credit cards. Tomorrow? Creating even more financial paths for our customers (and their wallets) to succeed.

This year, Empower ranked #65 on Inc. 5000’s Fastest-Growing Private Companies list — our third year in a row cracking the top 100 — and was named by Forbes as one of the 25 Next Billion-Dollar Startups for 2024. Empower was also featured by Forbes on America’s Best Startup Employers list in 2023, and our Thrive line of credit product was named by Fast Company as one of 2022’s Next Big Things in Tech.

Empower is backed by Sequoia Capital, Blisce, and Icon Ventures. Ready to grow your impact and accelerate your career? Take a look at our open roles — we can’t wait to meet you.

Empower is searching for a talented and highly analytical data scientist to manage the entire machine learning model development process from conception to deployment with business and engineering stakeholders, including creation of model pipelines, technical development, business validations, implementation and monitoring for our lending products issued by Empower Finance in Mexico.

Empower Mexico currently offers cash advances to consumers with loan amounts up to MX$5,000 and terms up to 41 days. Empower’s main business is in the United States with flagship Cash Advance, Line of Credit and Credit Card products. Empower also operates lending businesses in India and the Philippines.

The ideal candidate is passionate about using data and analytics to drive business growth and help customers improve their financial situations. The right person for this role is someone who shines while solving complex problems with accuracy and attention to detail. This role requires strong familiarity with SQL, Python, statistical analysis, and machine learning. This role will report to Head of International Data Science for Empower.

• Develop data standards, analytics pipelines, and new risk models for Empower’s business in Mexico to uncover novel insights that move our business forward

• Collaborate closely with the credit team to influence and use models that solve business problems, monitor business outcomes and enhance analytical tools

• Work with Empower Mexico’s leadership team to refine and execute the business plans and agenda.

• Partner with other credit and data science teams operating internationally and in the US to identify transferable learnings, strategies, and synergies and help implement them.

• Partner with leaders in product, engineering, marketing, and finance to ensure that the team’s work fits within the larger picture

• Bachelor’s degree in Engineering, Computer Science, or Mathematics

• 4+ years of industry experience in data mining, machine learning, statistical analysis, and/or predictive modeling

• Deep understanding of statistics and machine learning techniques, including regression, classification, clustering and optimization experience building predictive models from scratch

• Strong programming skills in Python with intermediate to advanced knowledge of SQL

• Demonstrable experience with ML packages: scikit-learn, LightGBM, XGBoost, SparkML, etc.

• Experience using LLM tools like Github Copilot, Cursor, or Claude CodeWindsurf to responsibly accelerate workflow. Understanding of the key tradeoffs between major model providers like Anthropic, OpenAI, and Google

• Knowledge in deep learning and experience with DL toolkits (Tensorflow, Keras, PyTorch) is preferred though not required

• Comfort working with a variety of cross functional partners in tech, product, credit, and business Exceptionally strong problem solving and communication with the ability to both get in the weeds and communicate to an executive audience

• Ideal candidate location is in Mexico.

1. Initial Recruiter Call: A conversation to learn about your experience and what you're looking for in your next role.

2. Hiring Manager Interview: A deeper discussion about your background and approach to solving challenges.

3. Skills Panel: Meet with Empower and NIRA team members to discuss your expertise and problem-solving approach through real-world scenarios.

4. Leadership Conversation: A final conversation with our CEO to discuss our mission and how you could contribute to it (and how we can help you achieve your career goals along the way).

Don't meet every qualification? If you're excited about this challenge and driven to innovate, we still want to hear from you!

• Meaningful Ownership: Competitive salary and generous equity in a profitable, fast growing company.

• Complete Support: 100% coverage for medical, dental, vision, and life insurance, plus a generous WFH reimbursement.

• High-Impact Teams: The chance to thrive in a small, focused team where your contributions directly shape outcomes for our business and customers.

• Remote First: A virtual first environment built on trust and outcomes.

• Team Connection: Twice-yearly company onsites where we come together to connect, learn, and build for the future (our last few have been in San Diego, Vail, and Flagstaff)!

• Growth Path: Ongoing opportunities for development in a dynamic, supportive, and creative environment.

The Empower Way is one where bold ambition meets an owner mindset, where open dialogue and spirited debate are encouraged, and where everyone works together to put our customers first. We believe diverse voices lead to the best ideas, and we foster an environment where every individual is valued, heard, and supported as part of one unified team working to change lives and build a more inclusive future.

If that sounds like you, join us and be part of a team that's helping millions of people reshape their financial futures.