Emissary is helping B2B companies better sell into the enterprise. We do this by providing sellers with high-touch, customer-specific sales intelligence. We have built a matching network to connect sellers with former decision-makers at the companies they’re trying to sell into. These ‘Emissaries’ act as deal coaches, providing insight at each phase of the sales process. As a result, Sellers close more deals, faster. The next phase of our growth is to build products that integrate our operational and matching processes into a delightful customer user experience that scales to meet demand for this service through establishing a marketplace and automated matching.

Backed by Google Ventures, Canaan Partners, and G20 Ventures, Emissary is the world’s first knowledge network for enterprise sales teams.

About the role

Emissary is seeking a Data Scientist to help our product and operations teams. Emissary is a B2B startup that is serious about data. We are seeking a Data Scientist who is eager to play a key leading data role on a results-oriented product team that delivers critical work for teams across the organization. A typical week may involve writing a custom data execution script, creating a new reporting query, and building a machine learning model.

What you'll do

  • Lead the end-to-end development and deployment of machine learning products (think user-facing matching engines, back-end data automations, etc); from deeply understanding the data, to building and tuning the model, to scaling it in production, you’re driving it.
  • Perform data analysis to extract  patterns and insights that help drive business decisions across our operations, and product teams
  • Continuously test and improve our current machine learning models in production
  • Mine our data for insights about evolving business needs, funnels and roadmap requests
  • Help maintain and continuously improve our existing business intelligence (BI) tools and underlying data infrastructure
  • Support ad hoc reporting needs

What we're looking for

  • Have 4 years of experience working on data analysis and 3-4 years of machine learning and modeling in a professional setting
  • Have a strong ability to code in Python, including the Pydata stack - we use Pandas, Numpy and SciKit-Learn
  • Have an expert level awareness of SQL and database concepts (we use Mysql and Postgres)
  • Have experience with statistics or machine learning on complex, noisy or sparse datasets to solve real-world problems
  • Love data munging
  • Are eager to expand your data science toolbox; you’re comfortable learning new tools and experimenting with new methods
  • Have the ability to distill ill-defined problems into clear and actionable ones
  • Operate with a high sense of urgency and enjoy working in a fast-paced environment
  • Can ship code and production-ready machine learning models
  • Very experienced in shipping functioning Machine learning models preferred
  • Experience shipping machine learning data pipelines and static trained models preffered
  • Ability to work independently and with limited supervision preferred

If this role sounds like you, please send along your resume and cover letter. We look forward to hearing from you!


Working at Emissary
Emissary’s mission is to transform the way the world gathers intelligence by empowering people to share their experiences.

Located in the heart of New York City’s Chinatown, we are a fast-growing tech startup with a scrappy, get it done mentality --  not to mention we were named a top NYC startup to watch in 2017.

We have great benefits - company and team lunches, Berkshires retreats, health/ vision and dental insurance, gym discount, 401k, healthy parental leave and more - but to us, the biggest perk is the opportunity to do great work with great people. To foster this great atmosphere, we take to heart these core values:

-  HONESTY: we believe in communication that is candid and straightforward while still being empathetic.
-  DIVERSITY: we seek to create a satisfying and diverse work environment.
-  THOUGHTFULNESS: we ask the tough questions and are always up for an engaged discussion.
-  EMPOWERMENT: we give people the ownership they need to do great work, and hold each other to high standards to get that work done.