Required Education:
Master's Degree or equivalent
Preferred Education:
Master's Degree in a Quantitative degree (Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities).
Required Experience:
5+ years experience translating business problems into data problems with different stakeholders or an equivalent combination of education and experience. Relevant training/experience in data science and/or statistical methods.
Preferred Experience:
2+ years experience in quantitative and qualitative research, statistical analysis, reporting, and/or data analysis of large, longitudinal data sets. Familiarity with the operational and business needs of a large higher education institution.
Required Skills, Knowledge and Abilities:
Demonstrated experience querying and processing large data sets. Demonstrated experience in statistical approaches to build predictive models (time series, clustering, neural networks) Demonstrated ability to tell stories with data using data visualization software or other reporting/BI tools (such as Tableau, PowerBI, ArcGIS, etc.). Demonstrated experience in programming/scripting languages and statistical software (such as R, Python, NumPy, pandas, scikit-learn, or PySpark). Demonstrated testing approaches for statistical and machine-learning analysis methods, software, and data sources for continual improvement of quantitative solutions. Demonstrated experience working with different file formats: CSV, JSON, Avro, Parquet etc., and data compression techniques Demonstrated strong verbal and interpersonal communication skills. Demonstrated proficiency in written communication skills. Demonstrated ability to communicate advanced analytical concepts and complex quantitative analysis in a concise, clear, and actionable manner. Demonstrated ability to respond to changing priorities and ensure timely, accurate deliverables. Demonstrated ability to work with diverse groups/populations. Familiarity working with cloud platforms & services (AWS, GCP or Azure)