Lead Data Scientist

Position Overview

• Location Type:
• Job Type:
• Salary:

Upgrade is a rapidly growing fintech company offering affordable and responsible credit, mobile banking, and payment solutions. Recognized by the Financial Times as the fastest-growing company in the Americas last year and with the Upgrade Card being the fastest-growing credit card in America for two consecutive years, Upgrade has provided over $33 billion in credit to 5.5 million customers. Backed by prominent tech investors and valued at $6.3 billion, Upgrade fosters an energizing, collaborative, and inclusive culture. The company has received numerous accolades, including "Best Place to Work in the Bay Area," "Top Companies to work for in Arizona," and recognition for its engineering department, diversity, women, culture, and veterans. We are seeking talented individuals excited about creating innovative products to join our team of 1850 professionals.

About the Role

Upgrade is looking for a highly analytical and results-driven Data Scientist to join its growing team in the financial services sector. This role is crucial for developing and implementing predictive machine learning/AI models, leading data-driven decision-making, managing data science projects from inception to deployment, and extracting insights to enhance product development, risk mitigation, and customer strategy. A strong background in statistics, machine learning, and financial domain knowledge is essential.

Responsibilities

• Build and deploy ML/AI models to address business challenges in areas such as prospect targeting, credit risk, fraud detection, pricing, verification, and loss forecasting.
• Analyze large, structured, and unstructured datasets using SQL, Python, or similar tools.
• Evaluate existing customer data and new third-party or alternative data to improve feature sets.
• Collaborate with data engineering and analytics teams to establish scalable and durable feature engineering processes.
• Stay current with the latest trends and technologies in data science and fintech, researching new tools and techniques for model development.
• Partner with cross-functional teams, including risk, marketing, product, and engineering, to define data-driven strategies.

Requirements

• Advanced Degree (MS/PhD) in Data Science, Engineering, Statistics, Mathematics, Computer Science, or a related quantitative field.
• 5-10 years of hands-on experience in a data science or analytics role, preferably within financial services.
• Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL.
• Ability to create clear documentation and present analyses to diverse audiences, from technical staff to business leaders.
• Detail-oriented with a strong analytical skill set.
• Proactive, driven, and capable of thriving in a fast-paced environment.

Nice to Have

• Experience in credit risk modeling.
• Experience designing and maintaining end-to-end CI/CD pipelines (e.g., using Kubernetes, GitHub Actions) for continuous integration, deployment, and monitoring, including automating model training, evaluation, and deployment workflows.
• Experience leading end-to-end machine learning and data science products from conception to development.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of big data technologies like Spark or Hadoop.
• Understanding of financial services concepts, including credit scoring, portfolio risk, or customer lifetime value.

What We Offer You

• Competitive salary and stock option plan.
• 100% paid