Parker Malek is a Programmer Analyst in Abt Associate's Natural Resources & Environment practice of the Department of Health and Environment. He has a strong background in atmospheric science, mathematics, computer programming, and data analysis. At Abt Associates, Mr. Malek has provided data quality, data analysis, and programming support to projects that span a number environmental and health fields.
Wobus, C., Zarakas, C., Malek, P., Sanderson, B., Crimmins, A., Kolian, M., Sarofim, M., et al. (2018). Reframing future risks of extreme heat in the United States. Earth's Future, 6, 1323-1335. https://doi.org/10.1029/2018EF000943
Data Science Certificate, Harvard University (2016-2018)
Programmer Analyst, CO-Benefits Risk Assessment (COBRA) Health Impacts Screening and Mapping Tool (Feburary 2018 - Present)
EPA's CO–Benefits Risk Assessment (COBRA) screening model is a free tool that helps state and local governments explore how changes in air pollution from clean energy policies and programs, including energy efficiency and renewable energy, can affect human health at the county, state, regional, or national levels, estimate the economic value of the health benefits associated with clean energy policies and programs to compare against program costs, and map and visually represent the air quality, human health, and health-related economic benefits from reductions in emissions of particulate matter (PM2.5), sulfur dioxide (S02), nitrogen oxides (NOX), ammonia (NH3), and volatile organic compounds (VOCs) that result from clean energy policies and programs. Abt Associates has created a local version of the tool, and are moving forward in producing an associated web tool for the application.
Responsibilites: Assist in developing a front end web interface that connects to a C# based backend version of the COBRA computing tool. TypeScript, CSS, HTML, and C# languages are utilized for this development.
Programmer Analyst, Federal Justice Statistical Program (FJSP) (2017 - Present)
Abt Associates has been awarded with a contract by the Bureau of Justice Statistics (BJS) to create an offender-level tracking system using data collected from the United States Marshals Service (USMS), Executive Office for U.S. Attorneys (EOUSA), Administrative Office of the U.S. Courts (AOUSC), United States Sentencing Commission (USSC), Pre-Trial Services (PTS), Federal Bureau of Prisons (BOP), and probation. The data is analyzed across the U.S. federal justice system from arrest through probation.
Responsibilites: Utilized SAS to create codebooks for each set of data; performing data quality checks; managing data from AOUSC and AO appeals; used Python's Selenium module to perform web scraping
Programmer Analyst. International pregnancy cohort study to evaluate the effect of influenza virus infection on pregnancy and perinatal outcomes and estimate the vaccine-preventable incidence of influenza during pregnancy among women in low- and middle-income countries (CDC) (2017–present) This prospective, longitudinal cohort study of pregnant women in low- and middle-income countries will be conducted during two influenza seasons in each country with three primary objectives: 1) to evaluate the effect of laboratory-confirmed influenza virus infection on pregnancy and perinatal outcomes among women in low- and middle-income countries; 2) to estimate the incidences of all-cause acute respiratory illness (ARI), febrile ARI, and laboratory-confirmed influenza virus infection during pregnancy; and 3) to examine the clinical spectrum of illness due to influenza viruses, including duration and severity of illness.
Responsibilities: Conducted data cleaning and analysis using SAS and R statistical software; Provided programming support for the data cleaning and analysis of summary tables for CDC.
- Wrote and quality assured Matlab scripts that perform extreme heat event analysis on CMIP5 temperature model outputs; Assisted in the production of figures using Matlab and ArcGIS; Provided support for literature reviews and scientific writing.
- Assisted in developing the TRI guidance document portion of the GuideME application; Utilized Python's Beautiful Soup module to produce Apex compatible database tables from HTML files; Added database tables to GuideME application; Updated application using PL/SQL and the Apex software platform.
- Worked on the OLYMPEX field campaign where I used the python programming language to analyze ground-based precipitation measurement data in order to assist NASA in validating and developing algorithms for a recently launched Global Precipitation Measurement Satellite (GPM)
- Maintained a version control that organizes data analysis from the department's rain gauge network on the Olympic Peninsula (R programming language)
- Assisted in field work where I am calibrating and deploying rain gauges to the Olympic Peninsula
- Wrote MATLAB scripts to process NETCDF files for flux tower site data analysis
- Created and presented a poster at the Undergraduate Research Symposium (Project Title: Determining a Relationship between Soil Moisture and Maximum Temperatures)
- Analyzed how a change in the light-use-efficiency of photosynthesis under different light environments contributed to the inter-annual variability of net primary productivity
- Incorporated and analyzed data from both flux tower networks and global climate model outputs (CASA model)
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