Sr. Data Scientist, Analytics
Vancouver, BC

Here's the gist:

The Role:

Data Scientists at Zenefits work on problems that are important to the company’s mission. Major challenges include developing systems and models that provide deep insights to employers about their employee population. Examples of insights could be predictive analysis on employee related attrition and churn analysis, comparative analysis of compensation info that allows employers to hire effectively. Data scientists are expected to apply machine learning and deep learning techniques to derive insights for customers of Zenefits.

In addition to developing the company’s core technologies, data scientists provide decision support analysis for many teams across the organization including product development, sales, marketing, finance and strategy.  Data scale ranges from small data sets to large multi-terabyte information in distributed database systems.

Responsibilities:

Qualifications:

Responsibilities:

  • Lead and develop major projects from end-to-end encompassing design, technical implementation, debugging, testing, and iteration
  • Operate at high degrees of competency and sophistication in statistics, machine learning, and computer science
  • Regularly write high quality code, perform code reviews, and produce excellent peer reviews on projects prior to shipping
  • Evaluate and experiment with new technologies and tools prior to wider adoption by the team
  • Work closely with data infrastructure engineers, data analysts, product managers, and engineers

A little more about you:

  • Lead and develop major projects from end-to-end encompassing design, technical implementation, debugging, testing, and iteration
  • Operate at high degrees of competency and sophistication in statistics, machine learning, and computer science
  • Regularly write high quality code, perform code reviews, and produce excellent peer reviews on projects prior to shipping
  • Evaluate and experiment with new technologies and tools prior to wider adoption by the team
  • Work closely with data infrastructure engineers, data analysts, product managers, and engineers

Nice-to-haves:

  • Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
  • Ability to explain data science models to technical and non-technical personnel.
  • BS with 8+ years or MS with 6+ years or PhD with 3+ years of experience.  Degree(s) should be in a technical discipline such as Computer Science, Engineering, Statistics, Physics, Math, quantitative social science
  • Work experience as an engineer highly desired
  • Experience with SQL relational databases as well as big data: the Hadoop ecosystem, Hive, Spark, Presto, Vertica, Greenplum, etc
  • Required: SQL, Python, linux shell scripting
  • Experience with machine learning and computational statistics packages (sci-kit learn, nltk, statsmodels etc)
  • Experience in deep learning techniques a plus
  • Experience with visualization tools (Mode, Looker, Domo, d3, Tableau, CartoDB, etc)
  • Frequent User of cloud computing platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  • Bonus Points for: experience with web application frameworks like Django

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