Senior Machine Learning Engineer
TLDR
Develop advanced machine learning models to enhance risk and fraud detection systems, while leading technical efforts and collaborating across teams to protect customers.
About Step
We stand for the side hustlers , the creators , the freelancers , and the investors . We are built for those who are looking to start early, to rebuild, or improve on where they are today. For people who are not afraid to take on challenges, especially when it comes to their finances.
Step is a next-generation financial services company building a better banking and borrowing experience to help people achieve financial independence as quickly as possible. We provide access to the tools, education, and opportunities to manage, build, and grow their money with confidence. Step is focused on disrupting the banking industry by delivering a differentiated, mobile-first consumer experience.
People love our product. We eclipsed over 7M million customers, and if you’re looking to join a fast-growing company with a strong mission and vision that puts people first, we want to meet you!
Step is a part of Beast Industries, a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most-watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains, including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.
The role
Step is looking for an experienced Data Scientist to build and deploy Machine Learning models for all things Risk and Fraud.
What you’ll do
- Build and Deploy ML Models: You’ll design, develop, and deploy machine learning models to enhance our Risk and Fraud detection systems. These models protect Step and our customers from fraud and financial loss.
- Lead Technical Efforts: You’ll take the lead in the Risk/Fraud area, providing technical direction and helping shape team’s strategy.
- Data Manipulation: You’ll use SQL to efficiently fetch, transform, and manipulate data, ensuring it’s ready for model development.
- Code Development: You’ll write production-grade code to deliver robust machine learning solutions.
- Design Experiments: You’ll apply statistics to guide experiments, determine appropriate sample sizes, and evaluate model performance.
- Cross-Function Partnership: Parter with Operations Team to quickly respond to rapidly evolving events.
What we’re looking for
- 5+ years experience in Data Science or ML Engineering
- Proficiency in SQL and Python
- Ability to communicate clearly with both technical and non-technical audiences.
- Excellent data analysis skills.
- Experience developing and deploying machine learning models.
- Experience, but not required, in working in financial systems, including lending or risk/fraud.
This role is available remotely within the U.S. or in our Palo Alto, CA office.
Working at Step & Beast Industries
We are building a next-generation consumer and services platform with global reach and long-term ambition.
Benefits
- Competitive Salary
- Generous Medical, Dental, Vision, and company-paid Life Insurance
- 401k Plan with Safe Harbor company-matching
- Flexible vacation policy and paid company holidays
- Company-provided technology package
Step is a financial services startup focused on enhancing the banking and borrowing experience to empower individuals on their journey toward financial independence. By leveraging innovative technology, it provides tools designed to make managing money simpler and more accessible for its users.