Bolsa de trabajo en Data Science

Descripcion

Haystack TV is the leading local & world news service on Connected TVs reaching millions of users! This is a unique opportunity to work at Haystack TV – named Best TV Experience by Google for 2017 along with Netflix and Red Bull TV. We are one the fastest growing TV startups in the world, and are already preloaded on 37% of all TVs shipped in the US! Be part of a Silicon Valley startup and work directly with the founding team. Jumpstart your career by working with Stanford & Carnegie Mellon alumni and faculty who have already been part of other successful startups in Silicon Valley.

You should join us if you're hungry to learn how Silicon Valley startups thrive, you like to ship quickly and often, love to solve challenging problems, and like working in small teams.

Job Functions
Haystack TV is looking for a versatile individual to join our team to lead all data science efforts.

Responsibilities include:

•Working on Haystack TV's recommendation engine and developing core IP
•Implementing well-architected, scalable production level code for new models and algorithms
•Using statistical analysis to make recommendations and drive product feature development
•Qualifications and Requirements
•Graduate degree (MS/Ph.D.) in Applied Math, Statistics, Computer Science, or related field
•At least 2+ year experience working on real-world statistical/machine learning problems
•Strong statistical and mathematical background.
•Proficient in at least one of the following languages - Python, C++, Javascript
•Familiar with SQL, MongoDB and/or other databases
•Experience writing production-ready code
•Excellent communication skills
•Experience in NLP preferred
•Proficient in spoken and written English
•IMPORTANT: Your job application has to be in English

We are passionate about creating amazing consumer experiences. We're a talented and experienced team that emphasizes giving everyone on the team a lot of ownership over what they are working on.

Salary open to discussion based on previous work experience.