Data Scientist

Job Description: - Collaborating with stakeholders across the organization to identify opportunities for leveraging company data to drive business solutions and outcomes. - Digging into and analyzing data from company databases to promote optimization and enhancement of product development, marketing strategies and business plans. - Evaluating the effectiveness and accuracy of new data sources and data collection techniques. - Giving assistance and collaborating with our product, sales, leadership and marketing teams, providing them with insights derived from analyzing company data. - Proficient in utilizing large data sets to discover opportunities for product and process optimization and using models to test the effectiveness of various scenarios. - Developing unique data models and algorithms to use on data sets. - Employing predictive modeling to boost and enhance customer experiences, revenue generation, ad targeting and other business results. - Creating a company A/B testing framework and testing model quality. - Collaborating with various functional teams to implement models and monitor outcomes. - Creating processes and tools to monitor and analyze model performance and data accuracy. - Designing Dashboards and Reports for Data Visualization (This includes utilizing tools like Tableau, Power BI, and similar tools to create interactive dashboards and reports). - Enthusiastically discovering solutions hidden within large data sets. Requirements: - Bachelor’s degree in computer science, business informatics, engineering, finance or any related fields. - 5+ years of experience, manipulating data sets and constructing statistical models, familiarity with the following software/tools: - Programming knowledge and experience in Java (Spring framework preferred). - Mastery of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and a deep understanding of their real world benefits and limitations. - Understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and their accuracy, etc.) and familiarity with applications. - Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. - Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and derive insights from large data sets. - Experience in retrieving data from databases and using statistical computer languages: R, Python, SQL, etc & utilizing web services: Redshift, S3, Spark, DigitalOcean, etc. - Experience in creating and utilizing advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. - Experience in analyzing data from 3rd party sources: 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 in visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc. - Experience in working with and creating data architectures. - Capacity and adaptability to learn and master new technologies and techniques. - Strong problem-solving skills with an emphasis on product development. - Excellent written and verbal communication skills for coordinating across teams.