Data Science

Full Time

San Francisco, CA OR REMOTE

Apply Now →

The Company

Dover is the modern recruiting department for the world's top companies. We combine domain expertise with best-in-class automation to help companies hire the best talent for their open roles.

Recruiting is a $50B industry in the US, but recruiting departments and agencies still have incredibly manual processes. Recruiters spend countless hours on administrative work, so they have less time to do what they do best: pitch and close candidates.

We've built a better way. Our advanced ML-powered matching software finds the perfect candidates for a particular role, and our NLP outreach system reaches out to those candidates in a highly personalized way. We're automating the entire recruiting stack, from sourcing to scheduling.

The Role

Dover is looking to hire our first data scientist. As a pioneer in the role, you'll have an outsized impact on our business & the chance to define data science at Dover.

Reporting directly to our CTO, your day to day work will involve interfacing with our engineering team and other C-level leadership to implement high leverage projects like improving our deep learning models. This is an opportunity for someone hands on to have total ownership over what projects you work on, and you deliverables. Depending on your desired area of focus, you can also help inform how we collect data and our data infrastructure.

Unlike many other companies, machine learning & data science is at the core of what we deliver, so you'll be using statistics and applying state of the art ML techniques to improve our core product. Your contributions will ultimately optimize customer experience and help us to figure out feature & product priority.

The Responsibilities

  • Build and improve machine learning and deep learning models
  • Work with the engineering team to ship models into production
  • Identify potential projects that could drive improvements to efficiency
  • Work independently to prototype new models & features
  • Being knowledgable about how to apply best practices to our data, not reinventing the wheel
  • Build playbooks and best practices to help us scale

About You

  • You've been working in data science/machine learning for 2+ years
  • Proficient in Python or a similar scripting language
  • You are comfortable doing feature engineering, scripting, and generally getting your hands dirty
  • You like moving fast and getting things done
  • Are an excellent communicator; verbal & written — with the ability to work cross-functionally
  • Experience applying machine learning or deep learning techniques to real world problems

Our Commitment to Diversity

At Dover, we are committed to building a team that represents a variety of backgrounds, perspectives, and skills. We do this because we know the more inclusive we are, the better our work will be.

Dover does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.

All employment is decided on the basis of qualifications, merit, and business need. We encourage candidates of underrepresented backgrounds to apply.

Benefits

At Dover, we think benefits should empower you to be your best, both in and outside of work.

Development

  • Competitive salary & meaningful equity
  • Support for workshops and lectures for personal & professional development
  • Opportunities to grow within the company

Wellness

  • Comprehensive health and dental benefits covered 100%
  • Reimbursements for physical & mental wellness
  • Daily lunch

Flexibility

  • All the tools you need to do your best work, including laptop, monitor, desk, chair, & more
  • Flexible work schedule and open vacation policy
  • Volunteer time off
  • Virtual assistant to take chores off your plate & help you focus on work

In addition to everything above, we do swag, birthday gifts, & host bi-weekly, socially distanced team events.

We prefer candidates in San Francisco, CA but will make exceptions for particularly strong candidates across the US and Canada.

Interested? Apply here →