Health Scientist (Data Scientist), CDC

These positions will be in a new Data Science team that is being formed in the Data Analytics Branch of the Division of Injury Response in NCIPC. This team members will apply data science methods that include artificial intelligence (e.g., machine learning), data linkage, data visualizations, and predictive analytics to various topics and priority areas of the Injury Center. There are multiple positions available across any of these job series.

Summary
The incumbent serves as a Health Scientist performing data science work that requires extraction of knowledge from public health surveillance systems and programs at the local, state and national levels that are structured or unstructured for analysis; improved understanding and communication; development/visualization of new concepts, and/or processes that add value to health services delivery and the decision making process.

Responsibilities
As a Health Scientist (Data Scientist), you will:

Consult and collaborate with statistical, data science, artificial intelligence (e.g., machine learning), and public health.
Plan and conduct research using public health data systems, including survey data, health care facility data, syndromic surveillance data.
Support the development of proposals and projects that align with research and policy goals for data science research and analytic projects.
Assist in monitoring data quality issues as they relate to user data products, and collaborates with Informatics and Information Technology.
Bring and develop expertise in the fields of health science, artificial intelligence.
Collaborate with other professionals within and outside the Center in the conduct of surveillance, research, and analytical studies.
Provide advice on the use of data science tools, methods, and statistical learning models to collect.
Maintain current knowledge of developments in allied health sciences, modeling, and machine learning analysis.
All other duites assigned.

Travel Required
Occasional travel – You may be expected to travel Domestic 5 % for this position.

For more information and to apply, click HERE.

Computer Scientist (Data Scientist), CDC

These positions will be in a new Data Science team that is being formed in the Data Analytics Branch of the Division of Injury Response in NCIPC. This team members will apply data science methods that include artificial intelligence (e.g., machine learning), data linkage, data visualizations, and predictive analytics to various topics and priority areas of the Injury Center. There are multiple positions available across any of these job series.

Summary
The incumbent serves as a Computer Scientist performing data science work that requires application of quantitative and qualitative research and analytics, statistical analysis, and building high quality prediction systems integrated with public health surveillance systems and programs.

Responsibilities
As a Computer Scientist (Data Scientist), you will:

Design experiments, tests hypotheses, and builds scalable data science models.
Conduct advanced data analysis and designs highly complex algorithms using artificial intelligence (e.g., machine learning) methods.
Lead discovery processes with stakeholders to identify business requirements and expected outcome.
Make strategic recommendations on data collection, integration, storage, access, analysis, and retention requirements.
Collaborate with CIO subject matter experts to select the relevant sources of information, which may include non-traditional datasets.
Work with stakeholders to identify the business requirements and the expected outcome.
Develop usage and access control policies and systems in collaboration with the IT security experts to ensure that the information used follows the compliance, access management.
All other duties assigned.

Travel Required
Occasional travel – You may be expected to travel Domestic 10 % for this position.

For more information and to apply, click HERE.

Mathematical Statistician (Data Scientist)- (Direct Hire), CDC

These positions will be in a new Data Science team that is being formed in the Data Analytics Branch of the Division of Injury Response in NCIPC. This team members will apply data science methods that include artificial intelligence (e.g., machine learning), data linkage, data visualizations, and predictive analytics to various topics and priority areas of the Injury Center. There are multiple positions available across any of these job series.

Summary
The incumbent serves as a Mathematical Statistician (Data Scientist) performing data science work that requires application of data mining techniques, statistical analysis, and building high quality prediction systems integrated with public health surveillance systems and programs at the local, state and national levels that are structured to add value to health services delivery and the decision-making process.

Responsibilities
As a Mathematical Statistician (Data Scientist)- (Direct Hire), you will:

Designs experiments, tests hypotheses, and builds scalable data science models
Develop experimental design approaches to validate finding or test hypotheses.
Identify relevant data available, including internal and external data sources, leveraging new data collection processes such as smart meters and geo-location information, or social media and unstructured web-based data.
Identify and analyzes patterns in the volume of data supporting the initiative, the type of data (e.g., images, text, clickstream or metering data).
Work with IT teams to support data collection, integration, storage, access, analysis, and retention requirements based on the surveillance data collected.
Work with stakeholders to identify the business requirements and the expected outcome.
Partner with researchers and subject matter experts to define the data quality expectation
All other duties assigned.

Travel Required
Occasional travel – You may be expected to travel Domestic 10 % for this position.

For more information and to apply, click HERE.

Statistician (Data Scientist), CDC

These positions will be in a new Data Science team that is being formed in the Data Analytics Branch of the Division of Injury Response in NCIPC. This team members will apply data science methods that include artificial intelligence (e.g., machine learning), data linkage, data visualizations, and predictive analytics to various topics and priority areas of the Injury Center. There are multiple positions available across any of these job series.

Summary
The incumbent serves as a Statistician (Data Scientist) performing data science work that requires application of data mining techniques, statistical analysis, and building high quality prediction systems integrated with public health surveillance systems.

Responsibilities
As a Statistician (Data Scientist) ( Direct Hire), you will:

Design experiments, tests hypotheses, and builds scalable data science models.
Conduct advanced data analysis and designs complex algorithms using artificial intelligence (e.g., machine learning) methods.
Identify relevant data available, including internal and external data sources, leveraging new data collection processes.
Defines the validity of information through automated systems and tools, how long the information is meaningful, and what other information is related.
Work with IT teams to support data collection, integration, storage, access, analysis, and retention requirements based on the surveillance data collected.
Collaborate with the data steward to ensure that the information used follows the compliance, access management, and control policies.
All other duties assigned.

Travel Required
Occasional travel – You may be expected to travel Domestic 10% for this position.

For more information and to apply, click HERE.

Analytic Epidemiologist, Enteric Diseases Epidemiology Branch (EDEB) CDC

Seeking an analytic epidemiologist or a public health-oriented data scientist, statistician, or population biologist/ecologist with a PhD, MD, or DVM to serve as Analytics Team Lead for a group that addresses analytic priorities that include:
• Informing food safety policy and tracking progress toward food safety goals by analyzing large, complex databases from various government, industry, and public sources to estimate, for
bacterial enteric pathogens, the
o number of illnesses, hospitalizations, and deaths, accounting for limitations in surveillance and other data;
o percentage of illnesses acquired by each transmission pathway (food, water, animals, environment, and people);
o percentage of illnesses due to each source (especially food categories); and
o spatiotemporal changes in pathogens and sources responsible for infections
o assessing the possible role of changes in regulation, consumer preferences, food marketing, and pathogens in the trends in illnesses
• Incorporating epidemiologic data analytics into the genomic revolution
• Understanding and adjusting surveillance measures to account for the rising use of cultureindependent diagnostic tests in clinical laboratories that test specimens from ill people.

Background
This branch tracks the incidence of and determines risk factors for illnesses caused by Campylobacter, Escherichia coli O157 and other Shiga toxin-producing E. coli, Listeria, Salmonella, Clostridium botulinum, Shigella, Vibrio, Yersinia, and other known and possible bacterial enteric pathogens. The first four listed are a major focus because they cause many illnesses, hospitalizations, and deaths; are transmitted commonly by food; and are amenable to control by national food safety regulations and policies. Clinical laboratories send bacterial isolates from ill people to state health departments, where whole genome sequencing is conducted. CDC collects data on individual illnesses and outbreaks caused by these pathogens, often with detailed information about the person (e.g., demographics, exposures) and the pathogen (e.g., sequence type, antibiotic resistance, virulence factors). Congress, regulatory agencies, consumer groups, the food industry, and others rely on CDC data and estimates to target and evaluate control measures, and to track progress toward food safety goals. The Analytics Team assists with the design and conduct of epidemiological studies, including population surveys, matched case-control analyses, and other research projects, and uses traditional and advanced epidemiologic and statistical methods and software to conduct analyses, including regression, Bayesian methods, and machine learning.

Duties
• Supervise and mentor a team of doctoral and master’s-level epidemiologists and biostatisticians,
providing technical direction, advice, and guidance to staff and encouraging a team environment.
• Design and evaluate epidemiologic studies and data.
• Document analytic plans and modeling methods and publish scientific papers.
• Collaborate on projects within the Branch, across the Division, and with government agencies (especially food safety regulatory agencies).
• Develop reports and provide presentations to communicate technical information to nontechnical audiences.

Qualifications
Successful candidates will have a doctoral degree (PhD, MD, or DVM) and extensive training in epidemiology, biostatistics, or data science. Qualified candidates should have experience in the application of analytic methods, demonstrated by a relevant scientific publication record. Candidates should have demonstrated the ability to communicate effectively and work well in a collaborative and interdisciplinary environment. Knowledge of and experience with generalized linear mixed models, Bayesian methods, machine learning techniques, and other modern approaches to causal inference and statistical analysis is preferred. Strong computational skills are preferred (e.g., R, SAS, or similar software; BUGS, JAGS, or similar software; and special purpose software, e.g., @Risk or ArcGIS). An understanding of clinical infectious disease or experience in analyses of infectious disease data would enhance the application. For more information: Interested persons should send their resume/CV and a brief statement of interest to edebadminsupport [at] cdc [dot] gov by with the subject line: Analytics Team Lead. For more information, contact Beau Bruce, MD, PhD (lue7 [at] cdc [dot] gov).