Data Scientist (hiring ASAP)

Responsibilities for Data Scientist:

•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 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.
•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:

•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.
•Strong problem-solving skills with an emphasis on product development
•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.

We’re looking for someone with some in experience manipulating data sets and building statistical models, with a degree 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.
•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.