Biostatistician - Data Scientist - Riverside University Health System

Full Job Description

• Experience Biostatistician in complex statistical analysis and advanced biostatistical models,
• Ph.D. with emphasis in research and advanced statistics.
• History of research and publications in medical, biomedical, and epidemiology research.
• Experience in Population Health Research.

Meet the Team! Founded in 1893, Riverside University Health System Medical Center has grown into a cornerstone of healthcare excellence and medical education in the region.

Our highly skilled healthcare professionals and dedicated support staff are committed to delivering exceptional, state-of-the-art care to the diverse populations of Riverside County.

Located in Moreno Valley, our 439-bed Medical Center is home to a Level I Trauma Center, a Level II Pediatric Trauma Center, and the county’s only Pediatric Intensive Care Unit (PICU).

If you’re passionate about making a meaningful difference and helping others, RUHS Medical Center is the place for you!

For more information about RUHS Medical Center, please visit www.ruhealth.org

Requirements

Consultation with potential researchers on study design (variables, data, and data sources)Designs, organizes, and develops research plans on Medical topicsDevelopment and maintenance of data capture tools including creating surveys, developing forms and procedures, and conducting interviews and focus groupsWriting queries to extract data from local data sources including electronic health recordsExtracting data from national datasets Evaluating quality of datasets and manipulation into a usable formRunning assumption tests in configuring and recoding the data to match the client’s needs and address his/her hypothesisConducting Univariate and Multinomial Logistic Regression Analysis, and propensity scoring methods Research alternate statistical techniques to improve existing processesConfiguring tables and charts Helping prepare manuscripts for presentation and publication including authoring and editing the “methods and results” sections of abstracts and manuscriptsPresentation of results to stakeholders and in professional conferences Qualifications Education: Graduation from an accredited college or university with a bachelor’s degree in a field of applied research such as data science, computer science, mathematics, statistics, business analytics, psychology, software engineering, management information systems, finance, statistics, or a closely related field to the assignment that included 12 semester or 18 quarter units of coursework in data science, predicative analytics, quantitative research methods, or statistical analysis.

(A master’s degree from an accredited college or university in a related field may substitute for one year of the required experience.

A PhD in a related field may substitute for two years of the required experience.)Experience: Two years of 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.Knowledge of: Data extraction, transformation and loading (ETL) techniques; programming languages such as R, SAS, Python, and/or SQL; data visualization tools such as Tableau and PowerBi; one or more of advanced Machine Learning techniques such as Classification, Prediction, Recommender Systems, Anomaly Detection, or Optimization; cloud computing platforms such as AWS, Google Cloud or Azure; version control systems; basic understanding of natural language processing (NLP); security and confidentiality requirements for handling sensitive data; classical statistical analysis methodology and machine learning, including predictive and prescriptive modeling and optimization.Ability to: Visualize data to generate critical information and knowledge and effectively communicate findings to technical and nontechnical stakeholders to support data-driven program design, management and decision-making; apply machine learning techniques to big data systems (e.g., Spark and Hadoop) to largescale datasets; write SQL code using multiple tools such as SQL Server Management Studio or GUI programs that assist with developing queries and reports; organize, synthesize and analyze large amounts of information; learn and adapt to new artificial intelligence and machine learning technologies and techniques; organize, synthesize and analyze large amounts of information; manage multiple deadlines and priorities efficiently; and work collaboratively as part of a team.

Additional Information For questions regarding this recruitmentPlease contact Jeremy Holforty a (951) 955-5558 orjholfort@rivco.org. Please allow 1-2 business days for a response to general inquiries.