Location: FCT-Abuja, Nigeria

Reports to: Programs Manager

About ACE Group 

ACE Group is a mission-driven consulting and non-profit organization committed to eliminating health and social inequities across Africa. We combine systems thinking, research implementation, and impact measurement to design contextually relevant solutions that scale and endure. Our core capabilities include strategy and systems design, program implementation, monitoring, evaluation, research and learning (MERL), digital innovation, and knowledge translation. Through these capabilities, ACE Group partners with organizations, donors, governments, and communities to strengthen systems, drive innovation, and advance equitable outcomes across the continent.

BACKGROUND

Family Health remains central to Nigeria’s healthcare system, addressing maternal and child mortality, malnutrition, and reproductive health. Although progress has been made, significant gaps persist in achieving Sustainable Development Goal 3 (Good Health and Well-being), requiring more coordinated and targeted interventions. While various efforts have contributed to improvements in maternal, neonatal, and child health (MNCH), family planning (FP), and nutrition outcomes, fragmented implementation has limited collective impact and missed opportunities for integrated, end-to-end service delivery across the continuum of care.

The Family Health portfolio manages and synthesizes large volumes of program data reported by multiple implementing partners across supported states and health facilities, spanning service delivery, commodity availability, healthcare worker capacity, facility reporting and other program indicators. To support this, ACE Group will coordinate and strengthen partner data management processes, including data validation, cleaning, harmonization, in-depth analysis, and the development of interactive dashboards, ensuring clear visibility of program performance and timely, evidence-based decision-making.

POSITION OVERVIEW

The Data Scientist will go beyond routine data management, visualization and dashboard development to interrogate program data, identify meaningful patterns, generate actionable insights and communicate these effectively to internal teams and clients. The role requires someone who can independently manage the full analytical journey, from data collection and validation through to insight generation and decision support, combining data engineering capability, analytical depth, programme thinking, and strong communication. Technical proficiency alone is not sufficient; the ideal candidate demonstrates genuine analytical curiosity and sound, independent judgement in interpreting programme data.

KEY RESPONSIBILITIES

Data Management & Quality Assurance

• Consolidate and manage large datasets received from multiple partners, states and facilities
• Assess data quality before analysis, including facility reporting rates, indicator completeness, missing data, inconsistencies, outliers and reporting gaps
• Determine whether available data is sufficiently robust for specific analyses and clearly communicate limitations
• Identify which datasets, indicators or facilities should be prioritised where data quality varies
• Establish structured data validation and quality-assurance processes for recurring partner reporting
• Design and maintain data models and joining logic that connect facility, state, indicator and time dimensions across partner datasets

Data Analysis, Modelling & Insight Generation

• Conduct retrospective, trend and predictive analyses across reporting periods
• Identify relationships and interactions between program indicators (e.g. commodity availability → service delivery → program performance)
• Investigate potential drivers of performance, including stock-outs, workforce availability, reporting gaps and facility-level factors
• Identify high- and low-performing states and facilities, and investigate the characteristics and enablers associated with high performance
• Detect unusual patterns or emerging program risks that require further investigation
• Apply appropriate statistical and machine learning techniques, including regression, classification, clustering and forecasting, to generate and test hypotheses from program data
• Translate findings into clear, actionable program recommendations, based on the analyst’s own independent interpretation of the evidence

Data Storytelling, Dashboards & Reporting

• Develop clear, decision-relevant dashboards in Power BI/Tableau that highlight what matters most, rather than simply displaying available data
• Produce concise written insights, analytical briefs and stakeholder reports
• Develop strong charts and visualisations that communicate program trends clearly
• Present findings confidently in internal and client-facing meetings, and explain technical findings to non-technical stakeholders
• Provide evidence-based recommendations on where program teams should investigate, intervene or prioritise resources
• Maintain documented, reusable scripts and dashboard/reporting templates for recurring use

DELIVERABLES

• Cleaned, validated and harmonised partner datasets with documented data dictionaries
• Data quality assessment reports, including reporting-rate and completeness scoring
• Trend, correlation, and predictive/forecasting analysis outputs across active programs
• Interactive Power BI or Tableau dashboards with drill-down functionality
• Analytical briefs and stakeholder reports with evidence-based recommendations
• Documented Python and SQL scripts, and dashboard user guides

QUALIFICATIONS & REQUIREMENTS

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Public Health, or a related quantitative field
• Minimum of 4–6 years’ experience in data science, data engineering or analytics, ideally within a program, public health or development context
• Advanced SQL, with the ability to independently write joins, aggregations and window functions across messy, multi-source, multi-partner data
• Strong Python proficiency: pandas and numpy for data wrangling; matplotlib, seaborn or plotly for visualisation; scikit-learn and stats models for statistical and predictive analysis
• Machine learning competency covering supervised and unsupervised learning (regression, classification, clustering) and time-series forecasting, using tools such as scikit-learn, stats models, and forecasting libraries such as Prophet or pmdarima
• Power BI or Tableau with calculated field/DAX proficiency, and strong Excel skills (Power Query, Power Pivot)
• Demonstrated ability to design data models and joining logic across facility, state, indicator and time dimensions
• Working familiarity with cloud data platforms, specifically Microsoft Azure or AWS, as partner and program data is currently stored across both; able to access, query and manage datasets in these environments without extensive onboarding
• Strong, independent analytical and statistical reasoning, with the ability to interpret data, test hypotheses and defend conclusions without relying on AI tools to perform the underlying analysis
• Experience designing data pipelines and validation processes for recurring, multi-source reporting cycles
• Proven ability to translate complex data into clear insights for non-technical audiences, including senior management and clients
• Familiarity with using AI/LLM tools to accelerate data cleaning, extraction from unstructured partner reports, or report drafting is an advantage. Candidates should be able to describe how they validate AI-assisted outputs and manage data governance considerations with sensitive program data
• Familiarity with Git or another version-control system is an advantage
• Knowledge of data governance, NDPA 2023, and ethical data management standards
• Strong written and verbal communication skills, with the ability to tell a clear story from data

DESIRABLE EXPERIENCE

• Experience working with international donors such as USAID, or UN agencies
• Familiarity with health systems data, routine health information systems (RHIS), or HMIS platforms
• Experience in program monitoring, evaluation, or research roles in the development sector