Cascade Data Labs
Portland, OR
Saturday, December 23, 2017
Based on Qualifications
Pay Type: 
Annually
40
1 September 2017
Full-time
No
No
No

Cascade Data Labs is always on the lookout for talent at all levels of seniority including internships.

We believe that good analysts have the vision to bridge the gap between stakeholder needs and the data available to them (no matter its condition). We’re highly selective in ensuring our consultants possess this foundational skill as well as the aptitude to execute it.

Successful applicants will have strong quantitative backgrounds and analytical discipline. While they will have some demonstrated ability to write code, they will not have learned programming languages for the sake of building their resume, but rather as a means to express their intellectual curiosity and analytical voice. Cascade Data Labs will provide a platform and training to help them reach their full potential.

Responsibilities

- Analyze a collection of raw data sets to create meaningful impact to large enterprise clients while maintaining a high degree of scientific rigor and discipline
- Build data pipelines to aid analysis and/or reporting
- Communicate findings in an intuitive and visually compelling way

Required Qualifications

- Bachelors or Masters in quantitative degree (Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities)
- Proficiency (can execute data ingestion to insight) in programmatic language such as SQL, R, Python (Pandas/Scipy/Numpy) OR at the very least, mastery level of Microsoft Excel

Preferred Qualifications

Candidates are not expected to possess all of the below skills but should possess a demonstrated aptitude and excitement to learn more of them.

- Proficiency in visualization/reporting tool such as Tableau, Spotfire, Qlikview OR proficiency in programmatic visualization library such as R, ggplot2, Python matplotlib/seaborn/bokeh, Javascript D3
- Proficiency in Microsoft Powerpoint or Keynote
- Proficiency scripting in UNIX
- Exposure to a big data environment and tools such as Hive, Impala, Pig, Spark, etc.
- Familiarity with AWS services
- Familiarity with machine learning techniques and libraries along with the ability to appropriately apply them to various business questions