Senior Quantitative Analyst / Modeler
Chase your aspirations with no boundaries at Leidos! Accelerate your career growth by joining Leidos.
Leidos has an opening for a Senior Quantitative Analyst /Modeler to support the Administration for Strategic Preparedness and Response (ASPR) within HHS in Washington DC. Be part of a small team with outsized impact! Perform a broad and ever-changing array of modeling, analysis, and data science projects supporting national health preparedness and the ongoing COVID-19 response.
Work as part of a multi-disciplinary team conducting a broad range of quantitative analyses. Examples include:
- Develop new forecasting techniques for infectious diseases
- Continue development of existing open-source agent-based modeling software framework
- 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
- Estimate the need for medical countermeasures to protect civilians from various threats, be they novel pandemics or use of CBRN agents
- Help senior decision-makers think through complex public health challenges
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 / decision-point as well as for briefing the methodology and outcomes.
You will collaborate with scientists from across the federal government, industry, and academia. Expect regular interactions with researchers from NIH, CDC, and the newly-established Center for Forecasting and Outbreak Analytics.
Telecommuting – Up to 100%. Preference for those local to Washington DC and able to take part in occasional on-site events.
- 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 novel statistical analyses of clinical trial results
- Performing the entire lifecycle of analysis: problem formulation, data acquisition, data cleaning, analysis, and presentation
- 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
- Ability to obtain and maintain a Secret clearance
- Subject matter knowledge of quantitative infectious disease modeling, COVID-19 epidemiology, and/or related sciences
- Subject matter knowledge of CBRN effects
- 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, Machine Learning/AI, statistics, disease transmission modeling, systems dynamics modeling, Data analytics, Bioinformatics, Health economics and/or economic modeling
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.