Responsible for executing a range of duties that support the core functions of the role, including managing project timelines, collaborating with cross-functional teams, ensuring adherence to company policies and industry regulations, and maintaining accurate documentation. Must possess strong analytical skills to interpret data, identify trends, and drive informed decision-making. Requires the ability to communicate clearly and persuasively, both in writing and verbally, to internal and external stakeholders. Must demonstrate proficiency in relevant software tools and systems, as well as the capacity to multitask effectively in a fast-paced environment. Additionally, accountable for fostering a positive work culture through mentoring junior staff, participating in professional development opportunities, and aligning tasks with organizational objectives.
Modeling & Analytics: Develop and implement advanced analytical models, leveraging statistical and mathematical techniques to extract actionable insights from complex datasets. Design and maintain robust forecasting systems to predict trends, optimize decision-making, and drive business performance. Utilize programming languages such as Python or R to build scalable solutions, ensuring accuracy, efficiency, and alignment with organizational objectives. Collaborate with cross-functional teams to translate data into strategic recommendations, supporting data-driven initiatives across the enterprise.
Support the formulation, implementation, and refinement of analytical and epidemiological models applied to HIV, malaria, and global health security initiatives, encompassing outbreak detection and scenario-based assessments.
Perform statistical analyses with standard statistical and programming tools to support international health research studies, program evaluations, and emergency response activities.
Provide analytical insights and modeling results to enhance situational awareness, evaluate risks, and support informed decision-making throughout outbreak response initiatives.
Conduct model calibration, validation, and error analysis while recommending and implementing enhancements to enhance predictive accuracy and operational effectiveness.
Mine and integrate diverse international data sources to construct essential indicators, calibration benchmarks, and analytical datasets, supporting strategic planning and performance tracking.
Facilitate analytical processes essential to monitoring and addressing outbreaks of global significance, such as emerging infectious diseases and public health crises.
Help assess the effectiveness of surveillance and early warning systems by analyzing key metrics such as sensitivity, response time, and data integrity.
Data Quality, Validation & Management: You will oversee the integrity, accuracy, and reliability of data assets by implementing robust validation protocols, conducting thorough quality assessments, and establishing standardized management frameworks. This role requires meticulous attention to detail, proficiency in data governance principles, and hands-on experience with validation tools and techniques. Your responsibilities will include identifying discrepancies, resolving data anomalies, and ensuring compliance with established standards and regulatory requirements. Additionally, you will collaborate with cross-functional teams to streamline data processes, enhance reporting accuracy, and support informed decision-making across the organization.
Develop scripts and production tools designed to clean, transform, and validate international health datasets, addressing discrepancies in completeness, timeliness, and data quality.
Monitor data integrity vigilantly to identify irregularities that could signal reporting inaccuracies, system malfunctions, or potential public health threats.
Conduct regular and specialized data quality assurance tasks to ensure accuracy and reliability for surveillance, modeling, and reporting initiatives.
Oversee or actively participate in the accurate entry, organization, and maintenance of data within programmatic, surveillance, and research databases to ensure data integrity and accessibility.
Developing and delivering clear, concise reports, visualizations, and presentations to effectively communicate insights and data trends to stakeholders at all organizational levels.
Conduct in-depth analysis of surveillance data, programmatic outputs, and model results, then translate findings into clear, actionable insights through technical reports, executive briefings, and concise summaries tailored for both internal teams and external partners.
Design visual representations—tables, figures, maps, and interactive dashboards using Power BI—to effectively convey key trends, potential risks, and data-driven insights to diverse stakeholders, ranging from technical teams to senior leadership and external partner organizations.
Employ GIS software, including ArcGIS, ArcGIS Online, and CGIS, to design and produce maps as well as conduct spatial analyses that facilitate the detection, monitoring, and response to outbreaks.
Develop and preserve geospatial datasets by integrating epidemiological, laboratory, and surveillance data pertaining to HIV, malaria, and global health security incidents.
Create static and dynamic maps designed to illustrate disease transmission, associated risk factors, health system capabilities, and the extent of intervention coverage.
Advanced analytical techniques, including clustering, hotspot identification, and proximity assessments, are utilized to enhance situational awareness and guide critical decisions during outbreaks of global significance.
Partner with cross-functional teams to transform geospatial data into polished visual outputs tailored for reports, executive briefings, and interactive dashboards.
Provide assistance in generating both regular and ad-hoc reports for initiatives focused on HIV, malaria, and global health security.
Facilitate and strengthen collaboration and partnership initiatives. Provide dedicated support to enhance relationships and ensure effective teamwork across departments and with external stakeholders.
Work collaboratively with epidemiologists, technical advisors, and program staff to advance international health initiatives.
Leverage collaborations with external partners, health ministries, and global organizations to facilitate seamless data exchange, comprehensive analysis, and accurate reporting.
Convey complex technical insights, analytical outcomes, and data constraints in an accessible manner to a broad range of stakeholders, particularly division leadership.
Bachelor’s degree in Computer Science, Information Technology, or a related field is mandatory, along with a minimum of five years of hands-on experience in software development, preferably within the IT sector. Proficiency in programming languages such as Java, Python, or C++ is essential, alongside a strong grasp of database management and software design principles. Familiarity with cloud platforms like AWS or Azure and version control systems such as Git is also required. Excellent problem-solving skills and the ability to work collaboratively in a team environment are necessary. Additionally, candidates must demonstrate strong communication skills to convey technical concepts to non-technical stakeholders effectively.
A bachelor’s degree in Public Health, Epidemiology, Statistics, Biostatistics, or a closely related discipline with a primary emphasis on global health security is required. Candidates holding a master’s degree in a relevant field will be given preference.
A minimum of seven to eight years of professional experience in applied data science and analytics is required, with at least two of those years specifically involving complex programming.
Requires advanced proficiency and hands-on experience in GIS applications to create detailed maps and perform spatial analyses essential for identifying, tracking, and managing outbreaks.
Proficient in distilling intricate datasets into clear, actionable insights and presenting findings in a compelling manner tailored to diverse stakeholders.
Exceptional analytical capabilities and problem-solving prowess are required, alongside meticulous attention to detail and a steadfast commitment to maintaining data integrity.
Educational qualifications beyond a high school diploma or its equivalent may fulfill the required experience, provided such substitutions align with the guidelines set forth by the JHU equivalency formula. Furthermore, relevant professional experience may compensate for additional education requirements, in accordance with the same stipulations.
Preferred Requirements: Demonstrates proficiency in SQL, Python, or R programming languages alongside practical experience with data visualization tools such as Tableau or Power BI. The ideal candidate should possess a Master’s degree in Data Science, Computer Science, Statistics, or a related quantitative field, supplemented by relevant certifications. Familiarity with machine learning frameworks and cloud platforms like AWS or Azure is highly advantageous. Additionally, experience in A/B testing methodologies, experimental design, or statistical modeling is preferred.
A master’s degree in Epidemiology or a related field is highly desirable.
Proficiency in R or Python programming is required, with a focus on leveraging generative AI tools and adhering to data reproducibility standards—such as those established by the tidy verse. Familiarity with data visualization techniques, particularly using plot, and version control systems like git is also essential.
Proficient in utilizing Excel for data analysis, reporting, and visualization tasks, with hands-on experience in DHIS2 for health information management systems, and skilled in leveraging Power BI for creating interactive dashboards and business intelligence reports.
Technical proficiency is essential in areas such as data architecture, management, and analysis, along with expertise in relevant data tools and platforms. Additionally, strong capabilities in data validation, quality assurance, and statistical modeling are required. Familiarity with statistical programming, data visualization techniques, and geographic information systems is also necessary. Proficiency in programming languages and foundational knowledge of machine learning are further prerequisites for this role.
Qualifications
BA/BSc/HND
