About the role

Join Self, a pioneering fintech company revolutionizing credit building and financial wellness for millions of underserved Americans. As a Principal Data Scientist on the Analytics & Data Science team, you'll play a critical role in building a data-driven culture and developing innovative solutions that empower customers on their journey to financial freedom.

Your work will directly impact millions of customers by shaping product & marketing development, personalizing user experiences, and driving financial inclusion. You will play a key role in establishing data science standards and maturity along with partners in Credit Risk Data Science, Architecture, and MLOps.

What you’ll do

• Use your machine learning expertise to tackle high-impact challenges like helping customers achieve their financial goals, developing a personalized financial recommendation engine, identifying transactions a customer can use to build credit, optimizing our marketing spend and segmentation, etc.
• Own machine learning models that impact metrics such as Marketing CAC, Conversion Rate, DAU/WAU/MAU, Retention, Cross-Sell, and RPU.
• Feature engineering utilizing data such as consumer behavior, clickstream, credit bureau, transaction history, etc
• Partner with Marketing, Product, and Engineering to drive model adoption and iterate on existing and future models based on business needs.
• Build the foundation for Data Science including standards, processes, and workflows
• Partner with Architecture and MLOps to deploy, monitor, and update production machine learning models
• Use your technical capabilities to drive growth and customer impact
• Stay up to date on the latest advancements in data science, machine learning, and AI
• Communicate complex technical concepts to both technical and non-technical audiences

The Ideal Candidate

• Cares about not only using the latest innovative techniques but that their work creates impact and change for customers
• Embraces ownership and drives things over the finish line autonomously
• Has demonstrable experience developing machine learning models that have driven notable incremental revenue and customer impact
• Has expertise in extracting and engineering key features from large data sets
• Is effective in navigating ambiguity to ultimately solve problems in a reasonable timeframe
• Is comfortable working in a small team setting
• Is an effective communicator to both technical and non-technical audiences
• Has prior experience with Fintech or building machine learning models within the Financial Industry

What’s exciting about the role

• You’ll have a direct impact on customers' ability to improve their financial lives via your machine learning/AI models
• You’ll have the ability to help build new products and experiences that directly impact millions of customers
• You’ll play a key role in establishing and scaling the data science and machine learning practice at Self
• Gain deep expertise in the fintech domain, working with unique datasets and cutting-edge technologies. Collaborate with industry experts and contribute to the advancement of financial technology
• You’ll work with a team dedicated to advancing analytics concepts and a culture that focuses on urgency, ownership, and collaboration
• You'll have the ability to execute autonomously
• You’ll have the chance to mentor teammates and build team culture
• You’ll learn how business decisions flow through the entirety of the business

What we want you to have

• 10+ years of Data Science / Machine Learning experience
• 5+ years experience with Git, Gitlab, Github, version control
• Advanced degree (Masters, PhD) in Computer Science, Mathematics, Statistics, Physics or a related quantitative discipline
• Strong expertise in data manipulation and analysis using SQL and Python, R, or similar
• Experience with AWS Machine Learning Services and a tech stack including s3, Glue, Redshift, Sagemaker, and Airflow
• Experience with libraries such as NumPy, SciPy, Pandas, Scikit-Learn, Matplotlib, etc
• Basic working knowledge of data warehousing, data modeling, and machine learning
• Experience with propensity modeling, lead scoring, clustering, recommendation systems, causal inference, genAI
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and influence stakeholders at all levels of the organization
• A self-starter mindset, with a strong sense of ownership, and the ability to work autonomously in a fast-paced, ever-changing environment

Base salary range: $180,000 - $200,000 annually. Individual pay is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.