Data Scientist Ii

Details of the offer

Our mission is to make higher education accessible and affordable for everyone. We empower students with financial support and supercharge their ability to pay down their debt, so they can get on the right financial track, fast.

We build tools that help people feel in control of their financial future, including:

Private student loans - low rates, people-first service, and flexible payments. Student loan refinancing - break free from high-interest rates or monthly payments. Scholarships - access to thousands of scholarships to help students pay less. Earnies are committed to helping students live their best lives, free from the stress of student debt.
If you're as passionate as we are about our mission, read more below, and let's build something great together!

The Data Scientist II position will report to the Manager, Data Scientist. As the Data Scientist II, you will: Design and implement ETL pipelines to ingest data from operational systems, third-party sources, and public datasets into the data warehouse, transform existing data for user consumption, and source data for model training. Extract data for model training from various sources, including data warehouses (e.g., Earnest, Navient), production databases, third-party providers, and publicly available datasets. Prototype machine learning models by applying best practices in feature engineering, model selection, and validation, while writing efficient code using popular frameworks such as Scikit-learn, TensorFlow, and PyTorch. Articulate to stakeholders the impact of the models and analyses through presentations and reports.
Draft recommendations for stakeholders that would optimize the product and underwriting policies. Your Impact: You will be responsible for guiding product recommendations and model development.
You will communicate analyses and results to the Data team backed by data and coupled with actionable conclusions to drive business decisions.
This role will be creating new analytical approaches, design efficient data querying and modeling development. About You: Bachelor's Degree in Computer Science, Data Science, Statistics or a related field. 3 years of experience developing traditional machine learning models using Python and applying advanced algorithms. 2+ years of hands-on experience working with data warehouse systems such as Snowflake, Airflow, and DBT to support data-driven model development. Willingness to travel to the Oakland office monthly to collaborate with other Earnies. Even Better: PhD in Machine Learning or very related topic, or Master's degree with equivalent experience with a minimum of 1-2 years of experience. Where: This role will be based in the San Francisco Bay Area. While you'll enjoy the flexibility of remote work, we also love to see our Earnies face-to-face!
We ask you to join us at our Oakland office for 3 consecutive days a month for team collaboration and some fun.
It's a chance to connect, share ideas, and maybe even grab some coffee together! Pay Range: $142,000 - $160,000 USD

Earnest believes in enabling our employees to live their best lives.
We offer a variety of perks and competitive benefits, including: Health, Dental, & Vision benefits plus savings plans. Mac computers + work-from-home stipend to set up your home office. Monthly internet and phone reimbursement. Employee Stock Purchase Plan. Restricted Stock Units (RSUs). 401(k) plan to help you save for retirement plus a company match. Robust tuition reimbursement program. $1,000 travel perk on each Earnie-versary to anywhere in the world. Competitive days of annual PTO. Competitive parental leave. What makes an "Earnie" culture: Drivers – Drivers are satisfied by making things happen, not coming along for the ride.
They feel a strong sense of ownership for their projects and teams and demand high standards from themselves and others. Humility – Humble team players check their egos and consider the team's needs above their own.
They are self-aware of their strengths and opportunities for improvement. Growth Mindset – People with a growth mindset approach challenges and failures as learning opportunities.
They seek feedback to improve, give feedback to others, and genuinely want to perform well. At Earnest, we are committed to building an environment where our employees feel included, valued, and heard.
Our belief is that a strong commitment to diversity, inclusion, equity, and belonging enables us to move forward with our mission.
We are dedicated to adding new perspectives to the team and encourage anyone to apply if your experience is close to what we are looking for. Earnest provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, veteran status, disability or genetics.
Qualified applicants with criminal histories will be considered for the position in a manner consistent with the Fair Chance Ordinance. Apply for this job * indicates a required field

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A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

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