Data Science Manager  

The Data Science Manager will be responsible for analyzing company data to support product, sales, and leadership and marketing teams.

• Adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
• Strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Able to work with a wide range of stakeholders and functional teams throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Must have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

• Education: Master’s Degree or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
  • Coding knowledge and experience with several languages: C, C++, Java,
  • JavaScript, etc.

• Experience: A candidate for this position must have had at least 3 years of working experience in data science capacity within a fast-paced and complex business setting, preferably working in a managerial role
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
  • Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
  • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
  • Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
  • Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.