1. Translate advanced business analytic problems into technical approaches that yield actionable recommendations,in diverse domains such as risk management, product development, marketing research, supply chain, and public policy; communicate results and educate others through insightful visualizations, reports and presentations.
2. Perform exploratory data analysis, generate and test working hypotheses, and uncover interesting trends and relationships
3. Retrieve, prepare, and process a rich data variety of data sources such as social media, news, internal/external documents, emails, financial data, legal data, and operational data.
4. Analyze and model structured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research.
5. Perform Statistical Natural Language Processing to mine unstructured data, using methods such as document clustering, topic analysis, named entity recognition, document classification, and sentiment analysis.
6. Work on implementing complex data projects with a focus on collecting, parsing, managing, analyzing and visualizing large sets of data to turn information into insights using multiple skill sets. These include code development and deployment, supporting data processing pipelines; data mining/science algorithms; and visualization engineering.