Data Scientist, Risk Analytics

Chicago, IL, United States

Who we are

M1 helps clients build and protect their wealth, day to day and for the long term. Our self-directed platform allows users to invest, borrow, spend and save in one place, using automation to power each user's unique personal strategy. Hundreds of thousands of clients trust us with over $7 billion in assets. As the Finance Super App™, we empower clients’ financial well-being through automated investing tools, industry-leading APY on high-yield savings accounts, paperwork-free margin loans, low-cost personal loans, and high cash back credit card rewards that can be automatically re-invested into your M1 portfolio.

Our vision is to create a digital private banking experience, making the tools and services of the ultra-wealthy accessible with the click of a button. We've been named a top app for investors including 2023 Best for Low Costs and Best for Sophisticated Investors by Investopedia, 2023 Best Investment App for Portfolio Customization by Insider and one of the best Roth IRAs by Fortune. We have over 60,000 five-star reviews on the Apple App Store and Google Play.

As a fast-growing fintech company, we’re looking for talented and smart individuals who are excited about rethinking what’s possible with personal finance, invested in their personal and professional growth, and eager to take ownership of their work. Our award-winning workplace culture has been recognized by Inc. (Best Workplaces 2022), Built In Chicago (2022 and 2023 Best Places to Work in Chicago), CB Insights (Top Fintech Companies of 2021), and the Chicago Tribune (2021 Top Workplace).

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

M1 is a remote forward organization and at this time is only able to hire in the following states: CO, FL, GA, IL, IN, MN, NJ, NY, PA, TX, UT, VA, OR, WA .

What we’re looking for

M1’s Risk Analytics team is looking for a Data Scientist to assist in analysis and model development as well as deploying and maintaining code in our loan decisioning system. This position will primarily focus on our lending s products as well as analysis and modeling related to general fraud risk.

The candidate will have the following or will have demonstrated the ability and willingness to learn the following:

A familiarity with financial mathematics. For example, you are familiar with present value calculations. You can understand and create a simple loan amortization table.

A strong familiarity with statistics and statistical analysis. For example, you are comfortable creating and interpreting linear regression models, or you are familiar with A/B testing and basic experiment design.

A strong familiarity with Machine Learning and predictive model development.

Production-level python coding and development skills. You can write clean, efficient code, unit test your code, and work with engineers to deploy the code in production environments.

An ability to grapple with complex business problems, interpret them into analytical problems, design build a solution, and work with cross-functional teams to put that solution to work. For instance, you can analyze fraud data and understand when a machine learning solution is warranted or when an analysis-informed rule set would suffice based on your measure of potential impact.

Writing skills sufficient to document models and processes for both internal stakeholders and external regulators and auditors.

Experience working with direct mailing campaigns, preferably in a financial services industry

The Data Scientist is someone who has a deep understanding of Advanced Analytics and Machine Learning. The role will include work on descriptive analytics as well as building predictive/prescriptive models and deploying  those models into production. A successful Data Scientist has demonstrated experience understanding business problems, identifying where models can help solve those problems, building models, and working with teams to make sure those models have a high impact.

What You'll Do

This position is within M1’s Risk Analytics team and focuses on credit risk and loan pricing as well as fraud identification, prevention, and mitigation. This role will also assist with analyzing and informing direct mail campaigns for lending products.

In this role you will:

Help determine loan pricing and underwriting strategies to balance growth and profitability:

Analyze the performance of past loan cohorts to estimate current and projected portfolio profitability. Analyze pricing relative to benchmarks and competitors. Help communicate results to stakeholders.

Improve M1’s loan pricing model using a combination of analysis-informed rule changes and predictive modeling.

Write python code to implement rule changes and models into production.

Write and maintain model documentation for approval by internal and external stakeholders.

Help create and maintain rules and models to improve fraud screening efficiency or reduce fraud losses.

Work with data analysts and fraud teams to understand types of fraud, how they are measured, and what interventions could improve efficiency.

Create and implement ML models to improve fraud detection and mitigation interventions.

Help improve direct mail campaign performance for our lending products:

Review analysis from data analysts and vendors on campaign performance.

Advise on A/B testing and experiment design strategies to improve audience selection and creative design.

Work closely with software engineers and data engineers on production deployment and data pipelines.

Work with compliance and accounting teams to ensure adherence to reporting and documentation requirements.

Have the opportunity to present analysis, findings and proposals to leadership.

Qualifications

Master’s degree in a quantitative field (like Economics, Mathematics, Statistics or Data Science) and at least two years of experience in a technical role. Alternately, a Master’s degree in a technical field (like Computer Science, Data Science) and at least three years of experience in a heavily analytical role requiring advanced analytics and strong grasp of statistics.

In lieu of a Master’s degree, a Bachelor’s degree in a quantitative/technical field and at least five years of experience in a relevant role demonstrating both quantitative and technical abilities.

Three years of experience using advanced analytics or predictive modeling to solve real-world business problems.

Demonstrated experience writing high-quality python code.

Demonstrated experience with a ML coding framework (e.g. scikit-learn) or auto-ML tool (e.g. Sage Maker, Dataiku).

Deep, demonstrated experience applying any of the following methods in real-world applications: causal inference, Bayesian data analysis, statistical experiment design, complex regression modelling and analysis, survival analysis.

Ability to explain complicated technical concepts to non-technical stakeholders.

Eagerness to learn new skills, tools, and subjects.

M1's Commitment to Diversity

M1 is proud to be an equal opportunity employer. We celebrate different experiences and we're committed to diversity, equity, inclusion, and belonging (DEIB) at all levels of the company. Women, minorities, veterans, members of the LGBTQIA+ community, and individuals with disabilities are strongly encouraged to apply. With our DEIB Council and six Employee Resource Groups (AAPI@M1, Black@M1, Mental Health@M1, Pride@M1, SomosM1, and Women@M1), M1 employees and leaders set aside company time to tackle DEIB projects and achieve goals every quarter.

Our Values

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

Mission Driven - We know that financial well-being has a dramatic impact on an individual's quality of life. We are passionate about helping people in this domain.

Extreme Ownership - We are responsible for the results to our clients, teammates, and shareholders. We own everything in our domain that affects these results.

Boldness - Thinking small is a self-fulfilling prophecy. Thinking big inspire results. We would rather fail at the meaningful than succeed at the trivial.

Ruthless Prioritization - We want to do more than we possibly can. We must be disciplined on how to use our precious money, people, and time. That means saying no to a lot of good ideas so we can focus on the most important thing.

Integrity - We do the right thing. This trust must never be broken.

Effectiveness - We do what's needed to deliver the intended results. Whether that requires disciplined process or scrappy implementation, we find a way.

Team Oriented - We work collaboratively to achieve more. We respect, trust, and support one another.

Transparency - We use simple and clear communication to share information so that people have the context to make good decisions.

Make Forward Progress - Something is better than nothing. We make incremental improvements on our path towards perfection. Crawl, walk, run, and then sprint.

Resiliency - We understand that any big goal comes with ambiguity, change, and setbacks. We adapt and keep going.

Our Perks

Competitive Pay and Stock Options

Comprehensive health, dental, vision, disability, and life insurance

Retirement benefit with employer match

Unlimited PTO

Office in the Loop with a Game Room and Gym

Access to employee workshops and training about financial literacy, empathy and mental health, professional development, and more

Free subscription to Insight Timer, the world’s #1 meditation app for sleep, stress, and anxiety