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Associate Director, Data Scientist

Princeton University

Princeton, NJ 08542

~ 33 min Onsite

7+ years of professional experience required in an analytical or information specialist role within an academic, nonprofit, corporate or consulting setting.
Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.
Keen desire to solve business problems, and to find patterns and insights within structured and unstructured data.
Expert in analyzing large, complex, multi-dimensional datasets with a variety of tools.
Accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS.
Experience with BI tools such as Tableau.
Having a good understanding of relational databases, warehouse design and architecture principles.
Familiarity with big data frameworks (e.g., such as Hadoop, Hive, Spark).
Good scripting and programming skills (e.g. familiarity with SQL, Python, Java).
Strong foundation in statistical, mathematical, predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find effective answers.
Familiar with disciplines such as: natural language processing, machine learning, conceptual modelling, statistical analysis, predictive modeling and hypothesis testing.
Able to create examples, prototypes, demonstrations to help management better understand the work.
Able to work autonomously.
Proficiency at planning and setting meaningful objectives to meet office goals. Ability to articulate and promote goals and implement strategic plans.
Education: Bachelor's Degree in operations research, applied statistics, data mining, machine learning, or a related quantitative discipline required.