Who we are 

M1 Finance has created a personal wealth-building platform made for the modern era, uniting personal perspective and automated ease. We seamlessly combine free investing, low cost borrowing and digital checking all in one intuitive, automated Finance Super App, and we’re driven by a mission to empower personal financial well-being. We believe that financial well-being is fundamental to overall well-being, and we strive to deliver products that are simpler, smarter, and stronger than those created by our staid, boring, entrenched, slow-moving competitors in the personal finance industry.   

Our clients have already trusted us with over $3 billion of assets, we’re currently helping more than 500,000 people grow and manage their wealth with our industry-leading automation and tools, and we’re adding thousands of new clients every day.  

We’re looking for passionate people who want to improve and build on what we’ve created and take responsibility to help others build something meaningful and sustainable for their futures.   

We mean it when we say, “M1 is yours to build.” 

If this sounds interesting to you, we’d love to have you read on. 

What we’re looking for 

M1 is looking for an experienced data engineer or data scientist to lead our production machine learning practice – someone who understands the unique challenges of building robust user-facing models; someone who knows the importance of methodology and intellectual discipline; someone who can solve hard engineering problems to deliver results at scale.  

At M1, data science is embedded within our larger engineering organization, working hand-in-hand with data engineering to deliver both insights and raw data to analysts and stakeholders through the organization. To achieve this, we rely on industry-leading tools - Kubernetes, a variety of AWS offerings like S3 and Redshift, and a Python-based programming stack.  

At M1, our engineering culture is committed to executing a clear and exciting vision. We adopt an iterative approach, believe in continuous improvement, and embrace first-principles thinking. While we value creative dissent in problem solving and eschew the idea of adopting a solution just because "it has always been done that way," we also believe in respect, support, and enabling each team members’ best contributions however we can. Everyone plays an integral part in developing our product and is empowered to make impactful decisions on features, architecture, and implementation.  

What You'll Do

• Predict business outcomes to better guide decision-makers 
• Develop a deep insight into the domain of personal finance to guide your work 
• Deliver results at production scale with automated pipelines 
• Integrate with our data warehouse and data lake to source the best input data available 

• Work closely with the brokerage, banking, marketing, and product teams to solve pressing problems 
• Implement clean and maintainable code that adheres to industry best practices 
• Automate processes to function robustly without manual oversight 
• Establish methods and metrics to validate models and ensure ongoing accuracy 
• Identify and execute on opportunities to improve existing systems 

• Contribute product ideas to overall company growth 
• Grow alongside an exciting, committed team who will always help you be your best 
   

Skills/Qualifications   

• 3+ years of experience in data engineering, data science, or similar fields 
• Bachelors or Masters degree in Computer Science, Data Science, or another quantitative field  

• Highly proficient with Python and SQL  
• Experience with Pandas, Scipy, and sklearn 
• Experience creating production-scale scoring, prediction, or recommendation systems 
• Experience with S3, Presto, Redshift, Spark, or other big data systems. 
• Experience with AWS, Kubernetes, or another cloud environment. 

• Demonstrated ability to collaborate with not only engineering teams but also stakeholders to deliver complex projects from start to finish 
• Strong mentorship skills with demonstrable experience elevating fellow team members 
• Entrepreneurial spirit, self-motivated, growth-minded 
• Excellent communicator and collaborator 
• General knowledge of investing and personal finance or desire to learn 

Preferred Qualifications  

• Knowledge of or interest in Scala 
• Experience with Apache Kafka, Amazon Kinesis, SQS, or other streaming data platforms. 
• Familiarity or interest in functional programming 
• Experience with agile project planning methodologies 

Our Values 

Our team embodies our eight core principles and if these principles speak to you – we’d love to talk with you.  

• Mission Driven: We will passionately apply ourselves to deliver immense value to our customers, knowing if they succeed, so too will the company. 
• Extreme Ownership: We think and act like owners. Our focus is on building long-term value, not scoring short-term marks. We own everything in our domain, including the outcome and everything that affects it. 
• Boldness: We want to do things of consequence. Make a difference. We would rather fail at something meaningful than succeed at something trivial. 
• Bias for action: The best way to make progress is to act.
• Economical: Efficiency is important, and we consider both the costs and benefits of our actions. 
• Team-oriented: In working together, we maintain a low ego, make everyone feel welcome, assume good intent, trust one another, and seek out different perspectives. We empower our teammates to be at their best.  
• Challenged, but not overwhelmed: We are curious people who always want to grow. Growth happens outside our comfort zone. We achieve our potential through consistent, manageable growth. 
• Integrity: We do the right thing. When we make mistakes, we own and correct them. We would be proud of our actions are shared with our family, friends, and strangers. Everyone can count on us to act according to our values, beliefs, and principles we state we hold. This trust must never be broken.  

Our Perks 

• Unlimited PTO 
• Comprehensive health, dental, vision, disability, and life insurance 
• Stock options for all employees 
• Retirement benefit with employer match 
• $500 to spend on home office equipment while working from home 
• Stylish M1 swag 
• Socially distant team outings, celebrations, and events 
• Transparent and open communication 
• Office in the Loop with a Game Room and Gym