We are seeking a data scientist to participate as a key team member in envisioning, designing, coding, testing and improving the algorithms that are central to our mission as a company.
Some key challenges will include:
- Identifying external datasets and developing API or other methods for accessing them
- Fluidly self-educating on existing methods for modeling end-user behavior in a variety of contexts, or developing new methods for doing this when necessary
- Designing experiments to answer targeted questions
- Teaming with developers to embed algorithms in applications
- Understanding business economics, user motivation and other contextual information in order to guide analytical trade-offs, with a focus on “minimum viable algorithm” followed by intensive, iterative improvement
The Successful Candidate
A successful candidate will be comfortable in a fluid, entrepreneurial environment, but one that is focused on developing reusable software applications, not bespoke analytical solutions.
He or she will likely have many of the following characteristics:
- 2+ years professional experience using statistical software (R, S-Plus, SAS, or similar), relational and NoSQL databases and scripting languages (such as Python). Ideally, R and Python
- Familiar with general-purpose machine learning methods, such as neural networks, Bayesian networks, regression, decision trees and so on. Capable of self-teaching new algorithmic methods easily
- Passionate about using data to drive strategy and business recommendations.
- Well-rounded top performer who is able to “crunch the numbers” one minute, and critically think through strategic issues the next
- Self-starter with a high degree of rigor, organization, and discipline to get things done
- Able to communicate as effectively in delivering complex data-driven findings with businesspeople, as in discussing machine-learning specifications with engineer
Very strong math, physics, CS or similar degree from a leading program
Extremely high SAT or similar standardized test scores