Minimum Qualifications:

• 3+ years of demonstrable expertise building and supporting machine learning models deployed to production
• Expert in Python and core libraries used by data scientists (Numpy, Scipy, Pandas, Scikit-learn, Matplotlib/Seaborn, etc.)
• Experience using Jupyter notebooks
• Experience working with large and/or noisy data sets

• Scikit-learn expert: This means you have rolled your own transformers and estimators, which you chained together in a pipeline and found optimal hyperparameters via a randomized grid search (or some other method).
• Pandas and Numpy expert: You have used pandas enough to run into its rough parts. You are fluent with Numpy and array oriented programming in general.
• Robust techniques: You are deeply familiar with different validation pitfalls, understand how to effectively ensemble several models, and have experimented with different hyperparameter optimization methods.
• Modern methods: You have built models using unstructured data such as text or images. You have built time series models using econometric approaches as well as machine learning approaches. Deep algorithmic understanding: You know all the nitty-gritty details of your favorite machine learning algorithms.

Additional details:

• Salary: We pay competitive salaries factoring in experience, skill set, and location.  We do not offer equity.
• We provide a wide-selection of health and welfare benefits including medical, dental, vision, life insurance, and supplemental income plans. We also offer a 401(k) Plan with a company match.
• Wellness and Time Off: We provide Headspace subscriptions, a wellness allowance, and generous time off including four weeks of PTO in the first year of employment with additional time granted upon hire. New parents may also take eight weeks of fully paid parental leave (plus four weeks for parents who give birth) which may be taken within one year after the birth and/or the adoption of a child.
• Professional learning and growth: We provide a generous allowance each year for professional learning, continuing education, and career development.
• Location: May work from anywhere in the US, but will need to be actively available during core meeting hours from 9:00AM - 3:00PM pacific time to collaborate with team members across all time zones. 
• Some travel may be required after the San Francisco office re-opens.
• Candidates based in the SF Bay Area will be able to commute to the SF office for in-person meetings and other gatherings. Frequency TBD.