The Global Data Science & Analytics Manager provides strategic and hands-on leadership in analytics, predictive modeling, data engineering, and data visualization across Living Goods and government partners. The role ensures that data is accurate, accessible, interoperable, and consistently used to strengthen frontline performance, inform policy decisions, and drive financing and accountability for community health systems. This position manages a global analytics team and works in close collaboration with the Digital Health (DH) Data team to design and deploy robust data pipelines, interoperable systems, dashboards, and decision-support tools. The Manager leads the development of advanced analytics products, builds internal and government capacity, and ensures that data-driven insights translate into improved supervision, operational efficiency, and health outcomes.
Key Responsibilities:
Analytics Strategy & Data-Driven Performance Management
- Lead the development and implementation of analytics approaches that support government-led performance management routines at county/district and national levels.
- Develop Community Health Worker (CHW) and supervisor performance analytics, risk stratification models, dashboards, and scorecards to guide decision-making and action planning.
- Ensure analytics priorities align with government needs, country strategies, program goals, and Living Goods’ strategic objectives.
Team Leadership & Capacity Strengthening
- Manage and mentor a multi-country analytics team including analysts, data engineers, and data governance staff.
- Build capacity of government counterparts, Monitoring, Evaluation, and Learning (MEL) officers, and program teams on dashboard interpretation, data storytelling, and use of analytics for supervision and planning.
- Foster a collaborative, learning-focused team culture that partners closely with MEL, Engineering, and Government Engagement teams.
Advanced Analytics, Predictive Modeling & Evidence Translation
- Lead the development of predictive models, geospatial analyses, segmentation tools, and performance optimization algorithms.
- Translate complex analytics into clear, actionable insights, dashboards, briefs, and recommendations for government and internal decision-makers.
- Support cost-effectiveness analysis, ROI modeling, and investment case development to inform financing and policy dialogues.
Data Governance, Quality & Interoperability
- Ensure strong data governance, quality assurance, privacy, and ethical data use practices across systems and countries.
- Work with government digital health teams to strengthen interoperability across eCHIS, DHIS2, EMRs, and other health data systems.
- Identify and mitigate risks related to data quality, model bias, security, and sustainability.
Partnerships, Collaboration & Influence
- Represent Living Goods in analytics, MEL, and digital health technical working groups, research consortia, and government coordination forums, ensuring alignment with LG’s data and digital health priorities.
- Build, maintain, and actively manage partnerships with Ministries of Health, academic institutions, digital health platforms, and implementing partners, with a clear responsibility to coordinate closely with the Digital Health (DH) Data team to ensure harmonized engagement, shared messaging, and unified technical assistance.
- Collaborate with the DH Data team to jointly design and deliver technical assistance on data systems, interoperability, dashboard development, and analytics for government partners at national and sub-national levels.
- Contribute to donor proposals, investment cases, and strategic reports, highlighting how advanced analytics and evidence generation—in partnership with the DH Data team—strengthen community health systems, improve data use, and support government-led digital transformation.
Qualifications & Experience:
Education
- Master’s degree in data science, Statistics, Computer Science, Health Informatics, Public Health, or a related field required.
- PhD preferred but not required.
Experience
- At least 7 years of experience in analytics or data science roles, including 3+ years in a leadership or team management position.
- Experience in public health, global health, or government health systems strongly preferred.
- Demonstrated ability to translate analytics into operational or policy decisions in real-world settings.
Technical Skills
- Strong proficiency in Python, R, SQL, and modern ML frameworks (e.g., Scikit-learn, PyTorch, TensorFlow).
- Experience with eCHIS, DHIS2, EMRs, or other health data systems is highly desirable.
- Familiarity with cost-effectiveness, ROI modeling, and health economics is an advantage.
Leadership & Interpersonal Competencies
- Proven team leadership and coaching experience.
- Strong communication skills, with ability to simplify complex analytics.
- Collaborative, adaptive, and comfortable working in fast-paced, multi-stakeholder environments.
Compensation:
A competitive salary and benefits package commensurate with experience including health insurance and bonus opportunity.
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