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Job Details


Senior Quantitative Epidemiologist / Modeler Consulting Employee

Technology

Senior Developer

Yearly

No

Reston, Virginia, United States

Description

Job Description:

Chase your aspirations with no boundaries at Leidos!

Leidos has an immediate opening for a part-time Senior Quantitative Epidemiologist / Modeler Consulting Employee to support the Administration for Strategic Preparedness and Response (ASPR) within HHS in Washington DC. Be part of a small team with outsized impact! The successful applicant will work closely with CDC’s newly-established Center for Forecasting and Outbreak Analytics on developing the nation’s next-generation disease forecasting capabilities.

Work as part of a multi-disciplinary team conducting a broad range of quantitative analyses, including:

  • Develop new forecasting techniques for infectious diseases
  • Continue development of existing open-source agent-based modeling software
  • Work with senior decision makers to translate policy questions into analyses
  • Work with development team to ensure that proper tools are available to support analyses
  • Perform healthcare cost-benefit and economic impact analyses
  • Perform data exploration on novel datasets
  • Construct visualization of large and complex data
  • Perform epidemiological analyses of infectious diseases
  • Assist clinical trial development with statistical analyses
  • Mentor junior analysts

You will work as part of a team on large-scale analyses as well as independently investigate problems. Many of these efforts have been recognized as being difficult to solve and require the sophistication, creativity, and judgment of an established and competent scientist. The position will require significant interaction with cross-functional teams of subject matter experts in non-quantitative fields, so communication skills are key to understanding the analysis needs as well as for briefing the methodology and outcomes.

Expected level of effort is 10-20 hours per week.

Telecommuting – Up to 100%.

Primary Responsibilities.

  • Working with customer to understand the decision points and refine a question into a task that can be answered with a model and the available data
  • Developing in and extending an agent-based framework to support infectious disease and other response activities
  • Performing ad-hoc analyses on existing data
  • Performing the entire lifecycle of analysis: problem formulation, data acquisition, data cleaning, analysis, and presentation

Basic Qualifications

  • MS in relevant discipline with 6+ years relevant experience OR PhD in relevant discipline with 4+ years relevant experience
  • Expertise in mathematics, probability and statistics, data science
  • Experience with scientific or mathematical software or programming; particularly R or other scripting language (e.g. Python, MATLAB, or Mathematica)
  • Experience developing software in an object-oriented programming language (Java programming is considered a strong plus)
  • Excellent communication skills with the ability to successfully interact with supervisors, functional peer groups, and/or outside customers

Preferred Qualifications

  • Subject matter knowledge of quantitative infectious disease epidemiology, COVID-19 / avian/pandemic influenza, and/or related sciences
  • Experience working with a data-science team, including knowledge of best practices of code management and working with large-scale data
  • Prior experience with Knowledge Data Analytics, quantitative algorithms for prediction and Machine Learning/AI Knowledge of statistics, disease transmission modeling, systems dynamics modeling, Data analytics, Bioinformatics, Health economics and/or economic modeling

Pay Range:Pay Range - -

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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