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 users.  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 real-time fraud detection for our digital banking business, to product recommendations at scale on our web and app platforms, to forecasting and anomaly detection systems;
work closely with our Data Engineering team to deploy these models across our Mobile App and Desktop & Mobile Web platforms;
collaborate with Analytics to design and analyze experiments testing the performance of our models;
build parameterized dashboards 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 Product;
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) team, Product, and others.



You’re a great fit for our team because…

You are strongly self-motivated, have a mindset of getting things done, and 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 (mainly scikit-learn and the Python API of XGBoost; experience with other packages is a plus) and algorithms (logistic regression, random forest classifier, gradient boosting regressor, etc.); experience with personalization algorithms and product recommendation systems is a big plus;
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;
(Plus) You have experience building machine learning models that were deployed as a service, with predictions being made in real time.



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 with many plan options;
we have team meals catered twice a week;
you can stay on top of your fitness goals with our on-site fitness centers and a monthly fitness reimbursement;
you can fuel up at our stocked kitchens with endless snacks and drinks;
we value EQ over IQ and prioritize work-life balance (read more about Credit Sesame’s Key Values here: https://www.keyvalues.com/credit-sesame)



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.

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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.