Research Software Engineer in Data Science

Location: Seattle, WA

Department: Data Science

Type: Full Time

Min. Experience: Experienced

Moz is looking for a Software Engineer for our Data Science team that enjoys writing clean, maintainable code to solve tough machine learning problems.  Generally speaking, we collect, process, and generate insights from a web crawl exceeding 25 Billion URLs each month.  You would be responsible for implementing algorithms that extract information from this data and analyze it in an efficient manner.  This is a great opportunity for a motivated self-starter who enjoys working through the implementation details of their ideas.  If large-scale data analysis is something you NEED to do, let's start the conversation!

About the position

The Data Science team works as an idea incubator inside Moz to prototype new features and evangelize them until they are in production.  We work closely with engineers on the Big Data and other teams to incorporate the initial prototypes into their existing services and products.

Some recent projects include:

  • Algorithmic spam detection (crawl 500B sub-domains and assign a spam score)
  • Dragnet (content dechroming: http://github.com/seomoz/dragnet)
  • Feed/Mention Authority (scoring RSS Feeds and recently created content: http://bit.ly/1k1tnOJ)
  • Social Authority (Twitter influence metric: http://moz.com/blog/social-authority)
  • Search volume estimation, topic modeling, customer segmentation/churn prediction, …)

Because we work on the bleeding edge of a lot of technologies, we need someone who problem solves creatively, learns quickly, and works productively both independently and collaboratively.  You would also gracefully and enthusiastically take on the following responsibilities:

  • Work with the Data Science and Big Data teams to integrate machine learning algorithms into production systems, all the way from prototype to production.  We use a mix of heuristics and ML techniques: linear/logistic regression, ranking models, clustering, LDA/topic models, etc.
  • Write clean, maintainable code.  We use git, Travis CI and Vagrant for our dev/test environment.
  • Process unstructured data into a form suitable for analysis (including web scraping, calling APIs, MySQL DBs, working with our in house data stores, etc, all at scale).
  • Take initiative, be a self-starter and awesomely creative.

Not to mention be comfortable doing all of this in the cloud!

Requirements:

  • Experienced SDE (Data Science/Big Data uses primarily Python and C++ [numpy/Cython/sklearn])
  • Someone who is interested in machine learning, natural language processing, information retrieval.  Direct experience not necessary, but a willingness/desire to learn and develop this type of software.
  • Experience working with and analyzing real world data at scale.
  • Familiar with Linux / distributed computing.
  • BS/MS/PhD in Computer Science, Math, Statistics or technical field / Excellent math/stat background.

About Moz

We build analytics software that gives our users the technical edge towards better marketing on the web. Behind the tool is a sea of Mozzers with a wide array of personalities, experiences, and expertise. We’re a startup with the ability to turn a profit, backed by a passionate community of followers, and with an exciting and hopefully VERY lucrative road ahead.

We’ve worked hard and deliberately to build a cultural roadmap. It’s not just about ping pong games and company parties (though we have those too!)— Learn more about it below before you apply:

  • Moz believes in the TAGFEE tenets. As Mozzers, we strive to exemplify these core values.
  • Making the web a better place (http://moz.com/about) and watch how we do it (http://moz.com/products).
  • Not convinced we are awesome yet? Check out our video “Why we love Moz”and our amazing benefits package.

Sneak peek at the goodies

  • Competitive salary, 401K, stock options
  • 21 days off plus 3000 per year towards your vacation!!!
  • Home internet and transportation subsidies
  • And so much more (feel free to grill us about the rest in the interview!)
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