Columbus, OH, USA
Position: Data Scientist
Location: Columbus OH
Who is "The Shipyard"?
The Shipyard is the home of marketing engineers. Here, the strange bedfellows of data science and creativity live in sin. Data geeks and creative storytellers share white boards, dashboards and storyboards with strategists, artists, developers to help brands solve extraordinary problems. And if you’re reading this, then you know we’re looking to expand our crew.
Who are you looking for?
The Shipyard is on the hunt for a Data Scientist to provide complex data mining and advanced analytical skills experience to our already exceptional team. This is a key role in the company that will help manage and analyze statistical data to provide expert advice that yields tangible results and provides business-boosting solutions for our clients.
What would I be doing day to day?
Use Google Analytics to create accounts, properties and views, implement tracking codes, build custom dashboards and schedule automated delivery, define goals and goal funnels, set up filters, set up event tracking, configure experiments and implement experiment codes, and create custom segments using regular expressions
Using Microsoft Excel to assimilate multiple data sources using index and match function, perform calculations using if-logic, including nested statements, and construct and manipulate pivot tables
quantitative analysis, including correlation testing (Pearson, Spearman, Chi-square, t-tests), regression (linear, multiple, logistic), clustering (k-means, Gaussian), and optimization (maximize, minimize)
Generating rollup reports using Adobe Omniture
Deliver weekly reporting to clients and provide analysis to help explain trends; proposing optimization strategies and solutions based on data collected
Working closely with Account Managers and our strategy group to ensure data integrity and consistency in reporting
Propose enhancements, modifications, and corrections to ensure reporting meets customer expectations.
Am I qualified?
Bachelor's degree or higher in computer science, engineering, mathematics, applied statistics, statistics or related field.
2 years of research and analysis experience in an academic or business environment.
Experience in the digital space, specifically in digital advertising.
2 years of experience in applied statistics or 3 academic semesters of statistics coursework.
Understanding of ETL (extract translate load) processes, including SQL, NoSQL, MongoDB, and Hadoop.
Proficiency in Microsoft Excel. Experience with Google Analytics, Google Webmaster Tools, Google Tag Manager, Demand Side Platform, and Data Management Platform.
Advanced Excel functionality, including: ability to write macros in Visual Basic for Application (VBA); experience with the Analysis ToolPak; and experience with Solver.
Experience preparing research findings for publication.
Knowledge of advanced quantitative methods, including mass statistical analysis, machine learning, regressions, clustering, neural networks, and descendants.
Experience or knowledge may be gained concurrently or as part of educational curriculum.