Earnest empowers people to live better lives

We're an accomplished team of design, math, finance and technology geeks who noticed some issues in our financial system and decided to do something about it. We created a company that combines data science, streamlined design, and technology to:

• Build more affordable products
• Bring them to more people
• Engage through more human experiences

As a Senior Data Scientist, you will report to the Head of Data and work on full stack-data science. Our modelers and engineers partner and own everything from data sourcing/ETL to model creation/testing and model deployment/maintenance. You will do compelling modeling and also work on state-of-the-art engineering.

Team Philosophy:

• Everyone on the team is considered and treated as a Senior, so you are given a lot of ownership over the projects you're working on. With this in mind, we expect you to write code that is well tested, modular, and maintainable. We frown at instances of destructive firefighting, caused by badly designed architecture or mismanaged projects.
• We like learners. Hence, we create an environment where Data Scientists learn the skills and abstraction patterns of Software Engineers and Data Engineers learn the iterative model development workflow seen in Machine Learning. Expect an environment where you will be always learning and challenged to work with tools, languages, frameworks that are outside of your area of expertise.

Tools, Frameworks, and Languages you will work with:

• Machine Learning: We use state-of-the art open source tools and frameworks. The problem domain is constrained to tabular, time-series, and NLP data.
• Languages: Python, SQL, R (occasionally you will also work with Node.js or Scala)
• Storage: Postgres, Redshift, S3
• Compute: Spark, Athena, EC2
• Workflow Management: Airflow
• Misc: Looker, Github, Jira, Splunk, PagerDuty

Responsibilities

• Creatively use new and existing data to increase the efficiency of our underwriting infrastructure
• Work with engineers to design machine learning solutions that operate quickly and effectively at scale. You will be involved in deploying models within Python microservices.
• Make recommendations to the executive and cross-functional teams that would help improve Earnest operations.
• Write tooling or expand on existing internal frameworks (e.g., feature-generator repo).

Ideal backgrounds and expertise:

• 3+ years of industry experience developing machine learning models from inception to business impact.
• Strong programming skills - Python preferred (though open to R for candidates that have very strong background in the language).
• Intermediate to advanced knowledge of SQL and ability to wrangle data from many different data sources.
• Deep experience with ML/DL toolkits: Tensorflow, scikit-learn, XGBoost, Numpy, Scipy, Pytorch, PySpark.
• You've earned a degree in Machine Learning, Statistics, Optimization, Physics, or related field, with experience building production-ready ML models and systems.
• Familiarity with building inferential models (GLM, LMER), simulation techniques (MCMC), and hypothesis testing.
• Understanding of traditional relational databases (PostgreSQL, MySQL) and distributed systems (Redshift, BigQuery, Spark, Apache Hadoop)

Nice to Have:

• Domain experience developing software for Fintech, Banking, or related Consumer Financial Services companies
• Kaggle Ranking (this can help speed up the interview process)
• An active Github or Medium profile

Earnest Perks & Benefits:

• Health, Dental, & Vision benefits plus savings plans
• Employee Stock Purchase Plan
• 401(k) plan to help you save for retirement plus a company match
• Tuition reimbursement program
• $1000 flight on each Earnie-versary to anywhere in the world and 25 days of annual PTO

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, disability, genetics, gender identity or expression, or veteran status. Qualified applicants with criminal histories will be considered for the position in a manner consistent with the Fair Chance Ordinance.