Job Title: Data Scientist
RTI International is seeking a Data Scientist for a USAID-funded malaria surveillance and monitoring project in Dar es Salaam, Tanzania. Monitoring will include entomological monitoring, including insecticide resistance monitoring, and therapeutic efficacy monitoring. Under the supervision of the Surveillance and MERLA Director / Deputy Chief of Party (DCOP) the Data Scientist will work with the other members of our team to provide state-of-the-art support for analysis and interpretation of epidemiological, entomological and drug efficacy data. S/he will carry out advanced analytics (predictive modeling, mathematical and simulation modeling, forecasting, text analytics, social network analysis) of malaria data. The Data Scientist will also support software development for data science applications, and support data visualization, particularly as it relates to dissemination of project data, findings, and achievements. S/he is expected to work closely with the Monitoring, Evaluation, Research, Learning, and Adapting (MERLA) Advisor, ICT Specialist, and RTI short term experts in MERLA, ICT, data science, and malaria epidemiology.
Essential Duties: Main purpose of job (List primary duties that occupy a majority of incumbent time in order of importance)
• Maintain positive functional relationships with all project stakeholders in Mainland Tanzania and Zanzibar, including the Ministry of Health, Community Development, Gender, Elderly, and Children (MOHCDGEC), Tanzania National Malaria Control Program (NMCP), National Institute for Medical Research (NIMR), Ifakara Health Institute, University of Dar es Salaam (UDSM), University Computing Centre (UCC), Zanzibar Ministry of Health (MOH), and Zanzibar Malaria Elimination Program (ZAMEP).
• Be fully engaged and connected to the wider HMIS/DHIS2 community to stay abreast of strategic, policy and technical developments.
• Serve as a member of and participate in relevant coordinating bodies, including the National Malaria Steering Committee, Tanzania Health Data Collaborative, eHealth Steering Committee, and their relevant sub-committees and technical working groups (TWGs).
• Carry out advanced analytics (predictive modeling, mathematical and simulation modeling, forecasting, text analytics, social network analysis) of malaria data. The Data Scientist will also support software development for data science applications, and support data visualization, particularly as it relates to dissemination of project data, findings, and achievements.
• Provide state-of-the-art support for analysis and interpretation of epidemiological, entomological and drug efficacy data. Data sources will include
(1) historical and current HMIS/DHIS2 data (collected at national, regional, district, and facility levels, and adjusted for reporting rates and changes in out-patient diagnosis attendance);
(2) nationally representative surveys (DHS, MIS, school malaria parasitological surveys);
(3) historical and current operational vector control (i.e., IRS, ITNs, larviciding), entomological and drug efficacy monitoring data;
(4) data on access to, use of, and adherence to other non-vector control malaria interventions, including case management; facility-based or community-based malaria prevalence and anemia surveys; and
(5) district-level lot quality assurance sampling of changes in malaria prevalence and intervention coverage estimates.
• Help to facilitate monthly MOHCDGEC and NMCP data use workshops to review, analyze, and interpret epidemiological and programmatic data reported through HMIS/DHIS2 and eIDSR.
• Support the MOHCDGEC and NMCP to define malaria outbreak thresholds and triggers.
• Continuously support ZAMEP to assess the sensitivity and specificity of these thresholds and triggers, and change and adapt these, as appropriate, to further increase interventions’ programmatic effectiveness.
• Contribute to assessments of other data platforms to determine whether they could be proxies for detecting malaria outbreaks.
• Help to establish and work with a Malaria Surveillance TWG to further integrate and strengthen the malaria surveillance and response system in Zanzibar.
• Contribute to the integration of an advanced malaria transmission risk model with the Malaria Case Notification (MCN) system in Zanzibar.
• Help to continue to adapt and enhance MCN reports and data visualization to meet emerging ZAMEP needs.
Minimum Required Education & Experience
Job Requirements are a combination of qualifications and related experience. Judgment of an acceptable equivalent combination, on an individual basis, is the responsibility of Management
• Master’s degree and 6 year of experience or Bachelor’s Degree and 10 years of experience or equivalent combination of education and experience
• Experience outside of a classroom environment with any of these: predictive modeling, machine learning, forecasting, optimization, text analytics/NLP, and simulation modeling
• Experience with modern open source software used in advanced analytics, software development for data science applications, and data visualization, such as: Python, R, d3.js, ggplot2, or Gephi
• Experience with SQL
• Strong interpersonal and collaboration skills – strong oral, written communication, and presentations skills as evidenced by publications or cover letter.
• Good team player
• Experience accessing, extracting, integrating, creating pipelines, and analyzing data from a wide variety of sources (e.g., relational databases, text and unstructured data, sensor data, social media data, image and video data, streaming data).
• Ability to quickly and easily learn new open source software
• An “analytical mindset” for solving problems
• Experience with static and/or interactive data visualization methods
• A strong sense of conceptual and visual design and creative problem solving
• Familiarity with SQL and NoSQL databases, including any of these: MySQL, PostgreSQL, SQLite, MongoDB, and Neo4j.
• Experience using git for version control, preferably while collaborating in a small team
• Subject matter expertise in health, epidemiology, and disease surveillance
Skills & Abilities
Skills and abilities required to perform the essential job duties of this job are listed below. An addendum that clarifies additional skills and abilities for incumbents in this job may be used in addition to this description
• Excellent knowledge of MS Word, Outlook, PowerPoint, Excel
• Ability to multi-task
• Ability to work well with others
• Ability to listen and communicate well both verbally and in writing
• Ability to work independently
• Attention to detail and accuracy
• Ability to obtain proper security clearances as noted by contracts
Physical and mental demands of this role include those that must be met by an employee to successfully perform the essential functions of this job, as outlined above. Examples include: remaining in a stationary position for long periods of time; operating a computer and other office machinery; thinking, learning, and concentrating effectively and frequently communicating with other people, both within RTI and outside of RTI; frequently moving about inside and travel between offices and laboratories; frequently conducting laboratory site inspections (if applicable), ability to handle the stress associated in meeting frequent, multiple and tight deadlines, ability to work in excess of 40 hours per week as workload and deadlines may require, ability to have regular, reliable and predictable attendance.
The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.
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