Responsibilities include:

• Mine data to support analytical projects and prepare data to support the development of information models to prove or disprove project hypotheses


• Use statistical analysis and machine learning libraries (R Stats, Python StatsModels, scikit-learn, etc.) to create models that quantify the influence of online activities on offline conversions


• Design and manage experiments to ensure proper execution, data cleanliness, and statistical significance of results


• Utilize data visualization techniques to explain data and models to clients and internal teams (Tableau, Looker, Data Studio, etc.)


• Nurture client understanding of the importance of building & testing strategies across media buys; act as a consultative resource to help clients understand the quality of their internal testing processes


• Integration of technology platforms and amalgamation of disparate client data sources


• Deploy cloud resources to perform analysis on large data sets

What you bring to it:

• 6+ years of work experience


• Strong analytical problem-solving skills and ability to work with incomplete or imperfect data


• Relevant mathematics background including Statistics, Calculus, and Linear Algebra


• Bachelor’s/Master’s degree in Computer Science, Engineering, Management of Information Systems, Mathematics, Statistics/Economics or relevant field


• 2+ years of experience in digital analytics and digital advertising


• 2+ years of experience querying large databases (SQL) (experience with BigQuery a plus)


• 2+ years of experience analyzing data with Python and/or R


• 2+ years of experience with site-wide analytics tool (Google Analytics/Adobe Analytics)


• Able to read/write basic HTML/HTML5/CSS/JavaScript


• Hands-on experience with machine learning algorithms for classification, regression, and prediction (example, scikit-learn, StatsModels, etc.)


• Experience reading the API documentation and understanding the technical requirements for implementation with other platforms


• Passionate about working in an extremely fast-paced, demanding, and innovative environment


• Ability to explain the analytical methods and results to non-technical stakeholders to drive data-driven decision making