Role and 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 productdevelopment, 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 targetingand 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 and Education Requirements
Strong problem-solving skills with an emphasis on product development.
Knowledge using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and drawinsights from large data sets. IBM SPSS Modeler would be an added advantage.2
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.
We’re looking for someone with knowledge of manipulating data sets and building statistical models, proficient in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Knowledge of querying databases and using statistical computer languages: R, Python, SLQ, etc.
Knowledge of creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.
Knowledge of analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Knowledge of with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Knowledge of visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.