Senior Technical Advisor, Analytics & Data at FHI 360

The Senior Technical Advisor - Data Analytics and Data participates in the provision of technical assistance aimed at strengthening collection, analysis, and use of data for decision making. The Senior Technical Advisor will supervise and utilize large data sets to find opportunities for improving program implementation, strategy optimization, and providing data-driven feedback to both the Government of Nigeria and the donor.

Duties and responsibilities:

• Determination of power and sample size requirements for studies - Cleaning, merging, and preparing analytic datasets
• Develop data analysis plans and prepare reports based on data analysis plans
• Work with stakeholders and the organization to identify opportunities for leveraging innovative technology/statistical models for business development.
• Mine and analyze data from company databases to drive optimization and improvement of implementation strategies.
• Develop custom data models and algorithms to apply to data sets.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Advise and assist in the development of inferences and conclusions, as appropriate.
• Use predictive modeling to increase and optimize program outputs.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Knowledge, Skills & Attributes:

• Strong problem-solving skills with an emphasis on innovation design and strategic frameworks using technology.
• Experience with Data visualization tools (Excel dashboard, Power BI and Tableau)
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• A drive to learn and master new technologies and techniques.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
• Knowledge of health and development programs in developing countries in general and Nigeria specifically.
• Knowledge of Nigerian clinical setting, including government and non-government settings.
• Sensitivity to cultural differences and understanding of the social, political, and ethical issues surrounding HIV infections.
• Ability to work well with others and to develop and maintain compatibility among project staff, subcontractors, consultants, and recipients of assistance.
• Ability to manage tight deadlines and deliver high volumes of work with minimal supervision.
• Excellent written and verbal communication skills in English for coordinating across teams.
• Ability to travel within Nigeria 25% time.

Qualifications and Requirements:

• Ph.D. in Computer Science, Computer Engineering, Health Information Management, Statistics, Mathematics or another quantitative field with relevant Professional Certification in Information and Communications, Technology, and related disciplines. 5 to 7 years relevant experience manipulating data sets and building statistical models.
• MSc in Computer Science, Computer Engineering, Health Information Management, Statistics, Mathematics or another quantitative field with relevant Professional Certification in Information and Communications, Technology, and related disciplines. 7 to 9 years relevant experience manipulating data sets and building statistical models.
• Experience using statistical computer languages (R, Python, SLQ, STATA, SAS, etc.) to manipulate data, querying databases, and draw insights from large data sets.
• Experience working with and creating data architectures.
• Familiarity with Nigerian public sector health systems and NGOs and CBOs is highly desirable.