Senior Data Scientist

Credit Sesame is a financial app for consumers who want to be confident their finances are under control. The platform uses AI to help consumers achieve credit health and financial fitness by managing and growing their credit and cash together. An all-in-one app to monitor credit score daily, receive insightful credit improvement and finance recommendations, and find the right credit cards and loans.

We’re seeking a motivated and experienced 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...

• 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;
• 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 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 are 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 experience building machine learning models that were deployed as a service, with predictions being made in real time;
• You have experience optimizing multi-step conversion funnels, spanning from impressions to clicks and ultimately to conversions;
• You are proficient at scripting in Python and in writing SQL queries (SELECT statements, mainly);
• You have deep knowledge of common machine learning libraries such as scikit-learn and XGBoost;
• You can work in a cross-functional team and manage multiple stakeholders;
• You have 6+ years of relevant experience, or a similar mix of experience and education in a quantitative field.

(Pluses) You have experience:

• Solving constrained optimization problems by leveraging business rules alongside machine learning models;
• 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 equity in a pre-IPO company backed by top VCs;
• we offer comprehensive medical, dental, and vision insurance;
• we offer a monthly home office stipend;
• we offer a professional development stipend to support your continued growth
• we offer flexible paid time off;
• we have 10 paid holidays and additional 6 Sesame Wellness days;
• we prize EQ and empathy, and have a culture that emphasizes total wellness, including work-life harmony.

At Credit Sesame, base pay is one part of our total compensation package. Actual salary will vary based on a candidate’s location, qualifications, skills, and experience. Additionally, this role is eligible to participate in Credit Sesame’s equity plan. The estimated pay range for this role in the San Francisco Bay Area is $160,000 - $190,000 and outside of the San Francisco Bay Area is $155,000 - $185,000.

We are open to hiring for this role in the following states where we are set up to hire employees: 

CA, CO, NC, NJ, NV, PA, and TX.