Job Description :
Job Responsibilities • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. • Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. • 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. • Coordinate with different functional teams to implement models and monitor outcomes. • Develop processes and tools to monitor and analyze model performance and data accuracy. Qualifications for Data Scientist • Strong problem solving skills with an emphasis on product development. • Experience using statistical computer languages (R, Python, SLQ, etc to manipulate data and draw insights from large data sets. • Experience working with and creating data architectures. • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc and their real-world advantages/drawbacks. • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc and experience with applications. • Excellent written and verbal communication skills for coordinating across teams. • A drive to learn and master new technologies and techniques. • Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc. • 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.