Associate, Data Science
Job Description
Job Posting Organization:
The Clinton Health Access Initiative, Inc. (CHAI) is a global health organization founded in 2002, primarily in response to the HIV/AIDS epidemic. Its mission is to save lives and reduce the burden of disease in low- and middle-income countries. CHAI collaborates with governments and the private sector to create and sustain high-quality health systems. Over the years, CHAI has expanded its focus beyond HIV to include infectious diseases such as COVID-19, malaria, tuberculosis, and hepatitis, as well as non-communicable diseases like cancer and diabetes. The organization operates in 40 countries and employs a diverse team dedicated to maximizing sustainable impact at scale, ensuring that solutions are government-led and designed for national scalability. CHAI values diversity and inclusion, recognizing that a variety of experiences and backgrounds enhances its mission.
Job Overview:
The Associate, Data Science position at CHAI involves working closely with the Ministry of Health (MOH) in Rwanda, specifically reporting to the head of data science at the National Health Intelligence Centre. The primary responsibility of this role is to enhance the quality, governance, and utilization of health data to inform policy decisions and improve health system performance. The Associate will lead advanced data analytics, statistical modeling, and applied machine learning initiatives across various public health domains. This role is crucial for transforming raw health data into reliable, actionable intelligence that supports AI development and decision-making processes. The Associate will also be seconded to the MOH/NHIC, emphasizing the importance of this position in the government's health priorities.
Duties and Responsibilities:
The duties and responsibilities of the Associate, Data Science include leading advanced data analytics and statistical modeling, developing and validating predictive models, and applying rigorous statistical methods to support decision-making. The Associate will ensure that all analytics are clinically interpretable and policy-relevant. Additionally, the role involves designing feature engineering pipelines, supporting AI engineers with training datasets, and contributing to machine learning model development. The Associate will lead the implementation of data quality frameworks, perform data audits, and ensure compliance with national health data governance standards. Furthermore, the Associate will develop decision-support analytics and public health dashboards, translate analytical outputs into policy briefs, and mentor junior data scientists and analysts. Continuous improvement and innovation in analytics and data science applications for public health will also be a key focus.
Required Qualifications:
Candidates must possess an M.Sc. degree in a relevant discipline such as Data Science, Applied Mathematics, Actuarial Science, Operations Research, Statistics, Epidemiology, or Health Informatics. They should have 5 to 8 years of professional experience in advanced analytics or applied statistics, preferably with applications in Data Science. A solid mathematical foundation and knowledge of various statistical methods, as well as proven experience working with large-scale datasets in regulated environments, are essential. Proficiency in data visualization and experience with programming languages such as Python, R, and SQL are required. Strong teamwork and communication skills are necessary for coordinating across teams and mentoring others in a dynamic environment.
Educational Background:
The educational background required for this position includes a Master’s degree in a relevant field such as Data Science, Applied Mathematics, Actuarial Science, Operations Research, Statistics, Epidemiology, or Health Informatics. This advanced degree is crucial for understanding the complexities of data analysis and statistical modeling in the health sector.
Experience:
The position requires candidates to have between 5 to 8 years of professional experience in advanced analytics and/or applied statistics, with a preference for experience in Data Science applications. This level of experience is necessary to ensure that the candidate can effectively lead data-driven initiatives and contribute to the organization's goals.
Languages:
While the job description does not specify mandatory languages, proficiency in English is likely essential given the international nature of the organization and the need for effective communication. Additional language skills relevant to the local context may be beneficial but are not explicitly stated as requirements.
Additional Notes:
The application process requires candidates to submit a CV and a letter of interest via email. The deadline for applications is October 12, 202
The Clinton Health Access Initiative, Inc. (CHAI) is a global health organization founded in 2002, primarily in response to the HIV/AIDS epidemic. Its mission is to save lives and reduce the burden of disease in low- and middle-income countries. CHAI collaborates with governments and the private sector to create and sustain high-quality health systems. Over the years, CHAI has expanded its focus beyond HIV to include infectious diseases such as COVID-19, malaria, tuberculosis, and hepatitis, as well as non-communicable diseases like cancer and diabetes. The organization operates in 40 countries and employs a diverse team dedicated to maximizing sustainable impact at scale, ensuring that solutions are government-led and designed for national scalability. CHAI values diversity and inclusion, recognizing that a variety of experiences and backgrounds enhances its mission.
Job Overview:
The Associate, Data Science position at CHAI involves working closely with the Ministry of Health (MOH) in Rwanda, specifically reporting to the head of data science at the National Health Intelligence Centre. The primary responsibility of this role is to enhance the quality, governance, and utilization of health data to inform policy decisions and improve health system performance. The Associate will lead advanced data analytics, statistical modeling, and applied machine learning initiatives across various public health domains. This role is crucial for transforming raw health data into reliable, actionable intelligence that supports AI development and decision-making processes. The Associate will also be seconded to the MOH/NHIC, emphasizing the importance of this position in the government's health priorities.
Duties and Responsibilities:
The duties and responsibilities of the Associate, Data Science include leading advanced data analytics and statistical modeling, developing and validating predictive models, and applying rigorous statistical methods to support decision-making. The Associate will ensure that all analytics are clinically interpretable and policy-relevant. Additionally, the role involves designing feature engineering pipelines, supporting AI engineers with training datasets, and contributing to machine learning model development. The Associate will lead the implementation of data quality frameworks, perform data audits, and ensure compliance with national health data governance standards. Furthermore, the Associate will develop decision-support analytics and public health dashboards, translate analytical outputs into policy briefs, and mentor junior data scientists and analysts. Continuous improvement and innovation in analytics and data science applications for public health will also be a key focus.
Required Qualifications:
Candidates must possess an M.Sc. degree in a relevant discipline such as Data Science, Applied Mathematics, Actuarial Science, Operations Research, Statistics, Epidemiology, or Health Informatics. They should have 5 to 8 years of professional experience in advanced analytics or applied statistics, preferably with applications in Data Science. A solid mathematical foundation and knowledge of various statistical methods, as well as proven experience working with large-scale datasets in regulated environments, are essential. Proficiency in data visualization and experience with programming languages such as Python, R, and SQL are required. Strong teamwork and communication skills are necessary for coordinating across teams and mentoring others in a dynamic environment.
Educational Background:
The educational background required for this position includes a Master’s degree in a relevant field such as Data Science, Applied Mathematics, Actuarial Science, Operations Research, Statistics, Epidemiology, or Health Informatics. This advanced degree is crucial for understanding the complexities of data analysis and statistical modeling in the health sector.
Experience:
The position requires candidates to have between 5 to 8 years of professional experience in advanced analytics and/or applied statistics, with a preference for experience in Data Science applications. This level of experience is necessary to ensure that the candidate can effectively lead data-driven initiatives and contribute to the organization's goals.
Languages:
While the job description does not specify mandatory languages, proficiency in English is likely essential given the international nature of the organization and the need for effective communication. Additional language skills relevant to the local context may be beneficial but are not explicitly stated as requirements.
Additional Notes:
The application process requires candidates to submit a CV and a letter of interest via email. The deadline for applications is October 12, 202
- The position is likely full-time and involves working closely with government entities, indicating a level of seniority and responsibility. CHAI is committed to data protection and requires consent for the collection and processing of personal data during the recruitment process.
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We are not liable for any decisions or actions taken by applicants in response to this job listing. By applying, you agree that all application processes, interviews, and potential job offers are managed exclusively by the listed employer or organization.
Beware of fraudulent job offers. Do not provide sensitive personal information or make any payments to secure a job.