Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company/opensource 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 modelling 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.
Education and Experience
Strong problem-solving skills with an emphasis on product development.
Experience using statistical computer languages (R, Python, SQL, 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.
We’re looking for someone with 2-4 years of experience manipulating data sets and building AI/ML & statistical models, has a Master’s 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.
Experience querying databases and using computer languages: R, Python, SLQ, etc. (Must)
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 with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.