Careers

Description:

Activity 1: Data

SUMMARY

This position will be a part of the core epidemiologist team implementing the surveillance system and COVID-19 response in Los Angeles County. This person will be working in a highly dynamic environment and managing numerous data flows and data tasks that necessitates a proficiency in Statistical Analysis Software (SAS) and being highly proficient in Structured Query Language (SQL), R, and Python, and familiar with ETL and pipeline automation. 

·         Candidates from outside of Los Angeles region are welcome to apply given current work from home environment, but must be available to work Pacific Standard Time (PST) hours

·         Remote/on-site depending on work needs and hiring manager’s discretion

·         Standard work hours (40hours/week)

This full-time benefitted position is grant funded through July 2021.  

Employment is provided by Heluna Health.

ESSENTIAL FUNCTIONS

The duties of the Data Scientist include, but are not limited to: 

·         Conducts COVID-19 specific epidemiologic analyses that involve large datasets, or linkage of multiple datasets, building and automating pipelines, and programming and comparing complex matching algorithms;

·         Database Management and liaising with vendors to build and manage database enhancement processes;

·         Building routine reporting mechanisms such as dashboards on trend analyses, descriptive statistics, and interactive geographic data displays;

·         Collaborates with division and department stakeholders to 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 various stakeholders to document business requirements and helps frame business problems so that appropriate corresponding data science techniques can be identified and applied.

·         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, Epidemiologists, 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.

·         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. 

·         Under supervision, relates or 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.

·         Complies with DPH training regarding confidential information related to personal information

·         Accepts responsibility for other duties as assigned.

JOB QUALIFICATIONS

Minimum Qualifications 

OPTION I: Four (4) years of experience applying advanced statistical analyses, including predictive analytics, to produce actionable recommendations to support data-driven program, policy, and operational decision-making in a clinical or public health field.

OPTION II: A Bachelor’s degree from an accredited college in a field of applied research such as Data Science, Machine Learning, Mathematics, Psychology, or Business Analytics that included substantial coursework in data science, predictive analytics, 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 degree from an accredited college or university in a field of applied research such Data Science, Machine Learning, Mathematics, Psychology, Epidemiology, Business Analytics or the equivalent may substitute for to two (2) years of experience.

OPTION III: A Doctoral degree from an accredited college or university with specialization in Data Science, Epidemiology, Machine Learning, Biostatistics