- Conduct statistical analysis of our audience web, demographic and transactional data in support of strategic initiatives.
- Project work covers all phases – conceptualization, planning, data acquisition, modeling, documentation, and presentation of findings/recommendations.
- Design tests, benchmark and track performance of predictive models over time.
- Improve business results, by applying machine learning to ongoing business activities, and develop recommendations to guide future activities.
- Work with partners in Data Engineering, Marketing, Product and Programmatic teams, to operationalize integration of analytic models into production environment(s).
- Stay current on relevant academic and industry developments to identify best-in-class algorithms, techniques, libraries, etc.
- Partner with other team members to evolve existing capabilities.
- Perform ad hoc analytic tasks and reporting as needed.
- Select features, building and optimizing classifiers using machine learning techniques
- Mine data using state-of-the-art methods
- Extend company’s data with third party sources of information when needed
- Enhance data collection procedures to include information that is relevant for building analytic systems
- Process, cleanse, and verify the integrity of data used for analysis
- Create automated anomaly detection systems and constant tracking of its performance
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Exceptional quantitative analytics/applied statistics skills, including regression, clustering and classification, forecasting and machine learning, and other techniques appropriate for large scale data analysis.
- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Exceptional programming skills in a modern-stack Linux environment. This includes knowledge of approaches to automate workflows and data pipelines.
- Experience with big data technologies: Hadoop, AWS/EMR, Spark, Hive.
- Two or more years of business/marketing analytics experience, preferably in a media organization.
- Exceptional communication skills, particularly in communicating and visualizing quantitative findings in a compelling and actionable manner for management.
- Strong set of professional skills: attention to detail; analytic, logical and creative problem solving; critical thinking; ability to work independently and within a cross-functional team.
- Advanced degree with an emphasis in a quantitative discipline such as statistics, engineering or mathematics.
- PhD preferred.