Senior Data Scientist - malaria and other infectious disease modeling experience preferred. Salary up to $152,000
Title: Senior Data Scientist
Salary Range: $117,191.00-$152,352.00
Application Deadline: Open until Filled
The U.S. President’s Malaria Initiative is the US Government’s (USG) flagship global malaria initiative led by USAID and implemented together with the Centers for Disease Control and Prevention.
To succeed in eliminating malaria, countries and their partners need to deploy the right resources at the right place and at the right time. By getting better, more accurate insights from existing data and accelerating the data-to-action cycle, countries and their partners can better respond to changes in on-the-ground conditions. That is why, in 2018, PMI began a major transformation toward greater use of data to inform decisions on resource allocation. As part of this new effort, PMI launched a new quarterly reporting process to ensure operational decision-making is based on timely and granular malaria data. In addition, at the headquarters level, PMI is developing a web-based data platform (“PMI Data Lake”) with analytics tools that will facilitate the triangulation and use of relevant datasets, including visualizations of epidemiological, supply chain, entomological, demographic, programmatic, and financial data. Building on decades of investments in malaria surveillance, monitoring, and evaluation, PMI is also expanding its support for the strengthening of malaria-related data systems and building institutional capacity within ministries of health and national malaria control programs to improve data quality and use.
As a key member of the Data Integration team, the Senior Data Scientist will provide subject matter expertise to support PMI’s increased focus on enhancing data-driven decision-making internally and externally within focus countries.
Specifically, the Senior Advisor will:
• Carry out rigorous, quantitative analyses and triangulation of data from a variety of sources (e.g. financial, programmatic, epidemiological, entomological, supply chain, demographic) to unearth implementation obstacles and opportunities, and employ cutting edge approaches and tools to generate compelling data visualizations.
• Undertake innovative applied statistical and computational methods and application of model-based statistics, addressing issues such as sample bias, spatial dependence, and model validation, to better map malaria related data.
• Implement, document, and test relevant computer code (in R, Python, C++, SQL or equivalent) to make the new methods and model features available to the broader team and broader audiences.
• Perform data quality checks on existing datasets used in epidemiological and statistical analyses and improve existing tools for automating data validation processes.
• Lead discussions and communicate highly technical information to both subject matter expert and non-expert audiences about quantitative analyses in order to interpret, vet, improve, and finalize results, and to formulate sound conclusions.
• Actively engage and coordinate efforts with the Malaria Modeling Consortium to integrate methods and results of separate workstreams.
• Provide technical and programmatic support to one or more PMI focus countries and participate as an integral member of one or more inter-agency country support teams.
• Provide guidance and support to Missions and PMI country teams on the development of annual country malaria operational plans and assist in monitoring and tracking overall progress of PMI plans and activities.
• Provide advice and technical assistance to Missions involved in malaria efforts, particularly the PMI-targeted countries in sub-Saharan Africa.
• Provide support to Missions by participating in country support teams, reviewing mission strategies and annual reports and helping them to meet needs for technical and programmatic support.
• Minimum of a Master’s degree (PhD preferred) in applied quantitative discipline such as, but not limited to, statistics, economics, computer science, ecology or epidemiology from a recognized institution.
• 9 Master's degree and 9+ years relevant experience or equivalent combination of education and experience or Bachelor's and 11 years.
• Practical experience in statistical inference, space-time mathematical models, or infectious disease modeling. Experience with machine learning and data mining
• Extensive experience with data wrangling, analysis and visualization using leading tools (such as at least of the following Tableau, Power BI, R, D3.js, or similar). Data analytics and visualization proficiency will be tested.
• Demonstrated ability to securely and efficiently manage large, disparate datasets, and problem-solving skills working on complex projects in a highly sensitive environment.
• Experience facilitating data analysis projects through rapid prototyping sprints, iterative design and execution, delivery and on-going support in a dynamic and agile environment with changing requirements and priorities.
• Experience with spatial data objects (e.g., shapefiles, rasters), survey data (e.g. DHS, MIS) and/or administrative data (e.g., HMIS, DHIS2) from health facilities is preferred.
• Ability to work under pressure and in teams.
• Ability and willingness to travel internationally, approximately 15%.
• US Citizenship or US Permanent Residency.
• Ability to obtain and maintain a Secret security clearance or at minimum a FAC.
- Non academic
- USAID | Bureau for Global Health | Malaria Division
- Washington, DC
- United States
- Closing date
- September 26th, 2019
- Posted on
- August 26th, 2019 18:59
- Last updated
- August 26th, 2019 20:37