DATA SCIENTIST - EMERGENCY APPOINTMENT (HOMELESSNESS)

• Collaborates with division, department, and countywide stakeholders to solicit, define, and manage data science projects from conception through implementation, including identifying and developing statements of business problems; conducting exploratory data analysis and data mining; developing model specification requirements; and conducting advanced statistical analyses.
• Develops and presents visualizations of findings and recommendations that can be used to support business decisions and allocate resources.
• Works with departmental stakeholders to document business requirements and helps frame business problems so that appropriate corresponding data science techniques can be identified and applied.
• Collaborates with department subject matter experts to understand, identify, and select available and relevant sources of data for use cases, including internal, external, structured, and unstructured data sources.
• Works with departmental Information Technology organization to support collection, integration, and retention requirements for large sets of structured and unstructured data from various sources and consults with data engineers and architects on the design and architecture of relevant data systems and processes.  
• Collaborates with other Data Scientists, Analysts, and IT staff to select, evaluate, improve, and document tools and systems in order to strengthen divisional and departmental analytic capacity.
• Independently conducts advanced analytical studies for the resolution of business problems and transfigures data into critical information by selecting and deploying appropriate advanced statistical techniques such as machine learning, bivariate and multivariate analyses, predictive/prescriptive analytics, and optimization.
• Uses statistical computer scripting, domain-specific, and programming languages and other software and tools to digest, manipulate, prepare, augment, evaluate, analyze, summarize, and visualize data.
• Plans, designs, and manages experiments, consumer surveys, and other data collection projects to augment existing sources of data as necessary to solve business problems.
• Reviews the work of Predictive Data Analysts and other lower-level analysts assigned to project for quality-control purposes.
• Conveys findings and conclusions of work orally, in writing, visually, in presentations, and by developing interactive tools as appropriate to communicate effectively with a wide range of audiences, including technical and nontechnical staff, stakeholders, and members of the public.
• 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 implementing recommended business process changes in ways that both retain fidelity to best practices identified through the analysis and recognize the operational realities underlying existing business processes.
• Works with functional teams to develop and implement products, services, and tools, such as dashboards and reports, emerging from the analysis.
• Contributes to advanced analytic products (e.g., Recommender Engines, Auto Classification algorithms, Predictive Scoring, geo-spatial clustering, NLP classifier, etc.) and helps place them in production.
• Recommends ongoing improvements to methods and algorithms that lead to findings, including new information.
• Provides business metrics for departmental projects to show improvements both initially and over multiple iterations.  Provides ongoing tracking and monitoring of performance of decision systems and statistical models and troubleshoots and implements enhancements and fixes to systems as needed.
• 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 pattern and trends from data.
• Develops relationships with local academic data science programs to foster recruitment of data science interns and is responsible for overseeing their work on departmental data science projects.

Option I: Two (2) years of experience applying advanced statistical analyses, including predictive analytics, to produce actionable recommendations to support data-driven program, policy, and operational decision-making, at a level equivalent to the Los Angeles County class of Predictive Data Analyst.*  

Option II: A Bachelor’s degree from an accredited college** 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- Four (4) years of experience applying machine learning, predictive analytics, data management, and hypothesis-driven data analysis to produce actionable recommendations to support data-driven program, policy, and operational decision-making.  A Master’s or Doctoral degree from an accredited college or university in a field of applied research such Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health may substitute for up to two (2) years of experience.

*Experience at the level of Predictive Data Analyst is defined as using machine learning techniques to analyze complex data sets and find statistically significant, meaningful predictive patterns, relevant to program goals, that human intelligence could not identify on its own.