Rarefied talent in data science, data technology, and analytics

Data Scientist (Decision Scientist)

MasterClass

Job Description

Who we are:

MasterClass is transforming online education by enabling anyone in the world to learn from the very best. We are deconstructing what makes an actor able to cry on demand, how an athlete defies gravity, and what it takes to write a bestseller. Our online learning content is available to students anywhere anytime. We are democratizing access to genius, one class at a time.

We are a fast growing VC-funded startup based in San Francisco and have created online classes taught by famous masters of their craft -- Serena Williams, Dustin Hoffman, Kevin Spacey, James Patterson, Annie Leibovitz, Usher, Christina Aguilera, and many more to come.

Since launching in 2015, we have been growing our team. Apply now to find out more about what we are doing behind the scenes.

What we are looking for:

  • Enthusiasm for working on projects across a broad range of analytic disciplines – from statistical analysis and predictive modeling, to user surveys and quantitative market research, to business intelligence and analytics.
  • A pragmatist, who is deliverable-oriented and a self-starter. You like moving fast and are not afraid to get in the weeds, but keep overarching objective and priorities in mind, which enables you to deliver a ‘good enough’ solution in a short timeframe when required.
  • Scientific mindset and desire to go beneath the surface and distill a problem into a clear set of hypotheses that can be tested.
  • Strong interpersonal and communication skills, including the ability to describe the logic and implications of a complex model to all types of business partners.
  • Comfortable with learning new tools or skills to remove bottlenecks and keep a project moving.
  • Good business acumen and product sense, and a penchant for systems thinking.

Responsibilities:

  • Perform data analysis to inform a broad range of decisions about the products and operations of the company, including some of the most impactful questions facing the business.
  • Help understand user behavior, preferences, and perceptions by conducting user research or analyzing user data.
  • Build predictive models; design, conduct, and analyze surveys and experiments; and conduct other analyses to answer strategic or operational questions.
  • Help the company make better use of data by extracting and making it easy to access the most actionable intelligence that can be derived from it.
  • Work closely with Product, Content, Marketing, Engineering, or other functions, as required.

Qualifications / Requirements:

  • At least two years of industry (i.e. non-academic) experience in data analysis, and preferably more.
  • Solid grasp of statistics and data analysis, including the ability to determine what is and isn’t a valid statistical inference, recognize & address biases, etc.  B.S. in statistics or applied math, or a highly quantitative background in social science.  Relevant M.S. or Ph.D. preferred.
  • Experience analyzing large and ‘messy’, real-world data sets, to answer questions about user behavior and discover insights, or to help improve the operations of a business.
  • Experience with building, applying, and evaluating predictive models.
  • Experience in designing and analyzing surveys, as well as analyzing results from qualitative customer / user research, strongly preferred.
  • Proficiency in use of SQL for extracting and structuring data (e.g. from PostgreSQL, Amazon Redshift, or other DBs).
  • Proficiency in the use of Python or R for processing and analyzing data.
  • Experience in the use of data mining and exploratory analysis.

Additional experience (not mandatory but we’d love to hear about it, if you have it):

  • Pricing analysis / pricing optimization.
  • Performance marketing analytics / conversion optimization (calculating CAC, modeling LTV, etc.).
  • Experience writing production-level code.
Interested in this position?
Job Location
515 Alabama Street
San Francisco, CA 94110
Additional Job Details
Employment Type:
Full Time