Data Scientist Machine Learning at Credit Sesame

Credit Sesame is the only platform that helps consumers achieve financial wellness by allowing them to manage and grow their credit and cash in one place, for free.  We have created a whole new market category in financial services that sits at the intersection of a credit market place and credit builder digital banking services.  Our purpose is clear, to make financial inclusion and wellness a reality for everyone.

We’re seeking a highly motivated Data Scientist to join our team and build predictive models that impact credit-related decisions made by millions of members.  This person will be responsible for developing, productionizing, maintaining, and monitoring ML models affecting all components of our business.


You'll...

Join a centralized Data Science team that is part of our larger Engineering org;
Use Python and SQL to develop machine learning models whose predictions drive many key aspects of our business, ranging from deciding which email to send to which user on each day, to product recommendations at scale on our web and app platforms, to forecasting and anomaly detection systems;
Work closely with our Data Engineering and MLOps teams to deploy these models across our Mobile App, Desktop, and Mobile Web platforms;
Collaborate with the Analytics team to design and analyze experiments which test the performance of our models;
Build parameterized dashboards (in Looker) to monitor both machine learning performance metrics and funnel metrics important to the business;
Initiate and lead new modeling projects as well as support initiatives spearheaded by the Product team;
Design and implement efficient pipelines both for model maintenance and for model deployment;
Pitch your ideas and present your results to stakeholders including our CRM (customer relationship management), Product, and Marketing teams.



You're a great fit for our team because...

You are strongly self-motivated, have a mindset of getting things done, are willing to pick up new skills as needed, and iterate quickly as appropriate;
You can communicate clearly and confidently to technical as well as non-technical audiences;
You have knowledge of machine learning packages (scikit-learn, XGBoost, etc.) and algorithms (logistic regression, random forest classifier, gradient boosting regressor, etc.);
You have knowledge of Python visualization libraries such as Matplotlib and Seaborn; knowledge of Plotly, Altair, and others is a plus;
You have experience translating machine learning predictions into actionable recommendations for solving practical business problems;
You have strong proficiency in writing correct and efficient SQL queries;
You are proficient at programming in Python, and at using Git (any other programming skills are a plus!);
You have 2+ years of relevant experience, or a similar mix of experience and education in a quantitative field;
You have knowledge of statistics and experiment design;
You are comfortable with being process-driven like an engineer, and purpose-driven like a business manager;
You can juggle multiple tasks in a fast-paced environment;
You can work in a cross-functional team and manage multiple stakeholders;
You can balance short-, medium-, and long-term objectives and successfully deliver on all fronts;
You want to work, excel, and grow in a diverse, challenging, and highly collaborative environment.



(Pluses) You have experience:

Building machine learning models that were deployed as a service, with predictions being made in real time;
Solving constrained optimization problems by leveraging business rules alongside machine learning models;
Optimizing multi-step conversion funnels, spanning from impressions to clicks and ultimately to conversions;
Building production-grade models for ranking content displayed to users;
Developing models that optimize for business outcomes (e.g., revenue) without resorting to localized, greedy optimization (e.g., maximize short term revenue without regard for long term effects);
Formulating and building models to predict customers’ Lifetime Value (LTV);
Predicting customer churn and/or retention.



You'll love it here because...

you‘ll have huge potential to grow with a company that’s a category leader;
you’ll have equity in a pre-IPO company backed by top VCs;
we offer comprehensive medical, dental, and vision insurance;
we offer monthly phone and internet reimbursement;
we prize EQ and empathy, and have a culture that emphasizes total wellness, including work-life harmony.



We're open to hiring remotely in both the US and Canada for this role. We also have offices located in Mountain View, San Francisco, and Toronto.



We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.