Nanigans is currently seeking an Optimization Analyst. This client facing role will require you to be analytically savvy and enjoy solving data-focused business problems including occasional programing. You'll be a full-stack consultant who will add value to the business by leveraging analytical, technical, and soft-skills to scale our SaaS platform. Example opportunities include: expanding the reporting api, building a data warehouse, optimizing our most strategic campaigns, interfacing with our data scientists, structuring performance tests, and analyzing/optimizing ad campaigns.
Writing scripts in programming languages such as Python or PHP
Distill complicated analytical concepts to a broad audience
Build and interpret regression models
Experience extracting data from relational (MySQL / SQL) or NoSQL (Hadoop / Hive) data stores
Experience coding in a unix environment using applications such as terminals, vim/emacs, and svn
Experience with Data Warehousing and related technologies such as ETL software (Informatica, Pentaho) and Visualization software (Tableau, GoodData) desired
Experience developing APIs
Experience with analysis tools such as Matlab, SPSS, or R
Experience in internet, financial, or consulting industries
Experience in Advertising Technology or Mobile a big plus
Math, engineering, or other quantitative bachelor's degree. Masters or PhD a plus
Proficient with Microsoft Excel including keyboard shortcuts, advanced excel functions, and pivot tables
At Nanigans, we are taking an active role in shaping the future of social advertising. We are looking for dedicated people with a strong sense of urgency and appetite to learn. In addition to our competitive compensation package, each full time Nanigans employee receives stock options, onsite product training, paid continuing education through Intelligently and top tiered health and dental insurance benefits. Backed by Avalon Ventures, our corporate headquarters is located in the heart of downtown Boston, with additional office locations in San Francisco, CA and New York, NY and London.