Jobs Companies Earnest Data Scientist

Sobre este puesto de Data Scientist en Earnest

Earnest · Remoto · San Francisco, CA (Remote)

Earnest empowers ambitious professionals to make confident financial decisions and build the life they envision.

Earnies are committed to helping borrowers move forward with confidence by offering smarter borrowing options with a clearer path to taking control of their debt. If you’re as passionate as we are about our mission, read more below, and let’s build something great together. 

Title: Data Scientist

Duties:

  • The Data Scientist at Earnest LLC in Oakland, CA will guide product recommendations and model development, and communicate analyses and insights to the Data team and broader organization. 
  • Develop and maintain predictive machine learning (ML) models to assess potential risks and opportunities across Earnest’s lending products, contributing to the enhancement of risk and marketing assessment procedures.
  • Participate in the end-to-end ML pipeline, spanning from data collection to model deployment. This includes collaborating with data and infrastructure engineers to automate training and monitoring using BI tools and writing ETL pipelines to source data for model training from various sources such as Earnest or Navient data warehouses, production databases, third-party providers, and publicly available datasets.
  • Conduct experimentation and execute causal inference analyses on pricing, marketing, and product models to optimize product conversion rates.
  • Write code for inferential models that guide product and underwriting decisions, and document modeling decisions through Confluence or GitHub Readme files.
  • Collaborate closely with cross-functional teams and stakeholders to accelerate solution iteration and achieve measurable outcomes.
  • Articulate model impacts and analytical insights through presentations and reports, draft recommendations to optimize product and underwriting policies, and provide guidance and mentorship on modeling best practices to peers on the team.
  • Position is 100% remote. Salary: $194,834 per year.  

Requirements: 

  • Master’s degree in Data Science, Statistics, Business Analytics, or a related field, plus 4 years of experience as a Data Scientist or related occupation.
  • Must have 2 years of experience with each of the following: (1) designing and implementing machine learning models, including regression, classification, and forecasting for applications including underwriting, propensity, or collections models; (2) SQL, Python, and R for data analysis, modeling, and automation; (3) product analytics and experimental design, including A/B testing and causal inference; (4) building, testing, and deploying scalable data pipelines and production-ready models using statistical and ML methods; (5)  researching and resolving data-related issues within the Financial Services, E-commerce, or Fintech sectors to drive informed decision-making and optimize business processes.

This notice is subject to Earnest LLC's employee referral program.

Interested candidates can online at www.earnest.com/careers [earnest.com] or send a resume to directrecruiting@earnest.com and reference job code 065. Contact Chayna Eno at people@earnest.com if you have questions or need information about this application.

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:

At Earnest, our people bring our cultural principles to life. These principles define how we work, how we win, and what we expect of ourselves and each other:

  • Every Second Counts: Speed is our competitive advantage. Our customers need better solutions, and the faster we execute, the greater our chance of success.
  • Choose To Do Hard Things: We win by tackling the hard things that others avoid, fueled by grit and resilience.
  • Pursue Excellence: Great companies, teams, and individuals never settle and are proud of the work that they do. What’s good enough today won’t be good enough tomorrow. Excellence isn’t a destination; it’s a mindset of continuous improvement.
  • Lead Together: Our success comes from how we work together. Leadership is not about titles—it is about action. We take ownership, drive results, and move forward as a team.
  • Don’t Take Yourself Too Seriously: We take our work seriously, not ourselves. The stakes are high, but a sense of humor keeps us grounded, creative, and resilient.

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.

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Cómo se compara este salario de Data Scientist

Este puesto paga $194,834/yren línea con el rango típico para los puestos de Data Scientist.

$169,166 la mediana de $213,757 $251,887

Rango típico $181,834–$216,358/yr, a partir de 18 ofertas comparables de Data Scientist en JobsRadar (salario anualizado en USD). Ver datos salariales de Data Scientist →

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