PREDICTIVE DATA ANALYST - EMERGENCY APPOINTMENT (HOMELESSNESS)

• Assists department stakeholders to define data needs and requirements to ensure data science projects meet business needs at the community, regional, divisional, departmental, or county-wide level.
• Collaborates with other department subject matter experts to understand, identify, and select available and relevant sources of data for use cases, including internal and external data sources.
• Collaborates with data administrators and other IT staff to develop data pipelines and ensure the availability of quality data.
• Uses statistical programming languages and packages, computer scripting languages, and/or domain-specific languages to digest, manipulate, prepare, augment, evaluate, analyze, summarize, and visualize data.
• Conducts end-to-end predictive data modeling projects that include basic exploratory data analysis, feature engineering, model selection, deployment of models into production environments, and visualization of findings.
• Uses advanced data visualization techniques to create data dashboards and reports to be used by varying levels of the enterprise and business managers.
• Uses supervised machine learning techniques on less complex business problems, with an understanding of algorithms, feature selection, variable importance, hyper parameter tuning, and optimization.
• Performs data management and manipulation, including the writing of data queries of departmental databases and data marts, data cleaning, and joining of multiple and disparate data sets.
• Extracts and organizes data and applies quality-control techniques to ensure the accuracy and completeness of all data; researches source documents and coordinates with others to resolve missing or conflicting data and other anomalies.
• Assists in planning, designing, and managing experiments, consumer surveys, and other data collection projects to augment existing sources of data as necessary to solve business problems.
• Works with program staff to understand the implications of analyses and to ensure that findings are actionable and support data-driven program, policy, and operational decision-making.
• Assists in coordinating with various functional teams to develop and implement products, services, tools, or business process changes resulting from the analysis.
• Accesses ongoing training and professional development to maintain familiarity with current industry and academic research to apply the latest and most useful statistical learning techniques to help extract patterns and trends from data.

Option I: A Bachelor’s degree from an accredited college or university* in a field of applied research such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health that included 12 semester or 18 quarter units of coursework in data science, predictive analytics, quantitative research methods, or statistical analysis -AND- Two (2) years of experience in the application of techniques of machine learning, predictive analytics, data management, and hypothesis-driven data analysis to complex experimental designs leading to actionable findings and recommendations -OR- A Master’s or Doctoral degree from an accredited college or university in a field of applied research such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health.

Option II:  Four (4) years of experience with responsibility for planning, designing, conducting, and evaluating research projects involving the application of techniques of machine learning, predictive analytics, data management, and/or hypothesis-driven data analysis to complex experimental designs leading to actionable findings and recommendations.