Data Lead

Job title: Data Lead (Monitoring, Evaluation, and Advanced Analytics)

Reports to: Executive Director

Start Date: ASAP

Hours: Full-time

Duration: 24 months, Renewable

Location: Lusaka (Primary); Hybrid – Office/Remote

Job purpose:

At BongoHive, we rely on insightful data to power our systems and solutions. We’re seeking a talented data scientist/analyst to deliver insights on a daily basis. The ideal candidate will have mathematical and statistical expertise, along with natural curiosity and a creative mind. While mining, interpreting, and cleaning our data, this person will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realizing the data’s full potential. As part of a team, the Data Lead will “slice and dice” data using various methods and create new visions for the future.

The Data manager will be required to enhance quality M&E, analysis and learning from project implementation by ensuring appropriate use of M&E frameworks and tools that assure quality programme and project delivery across BongoHive and partners’ projects. Additionally, will oversee the redesign of M&E and Data Analytics processes within the whole organization.

Objectives of this role

• Collaborate with other departments including the technology team to develop an understanding of needs.
• Research and devise innovative statistical models for data analysis.
• Communicate findings to all stakeholders.
• Enable smarter business processes by using analytics for meaningful insights.
• Keep current with technical and industry developments.

Duties and responsibilities:

Advanced Data Analytics and Database management work:

1. Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the IT team in the development of data products;
2. Execute analytical experiments to help solve problems across various domains and industries;
3. Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables;
4. Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy;
5. Analyze data for trends and patterns, and interpret data with clear objectives in mind;
6. Implement analytical models in production by collaborating with software developers and machine-learning engineers;
7. Design and maintain database systems and Dashboards that improve BongoHive’s ability to inform program/project implementation, analyze data, identify trends and present impact to key stakeholders;
8. Ensure all relevant programme staff are able to update and utilise the databases to analyze program information and results;
9. Manage project database to facilitate timely information updates, data quality assurance, sharing of information and learning, and data use for decision-making;
10. Prepare data reports (tables, charts, narratives, visuals) at regular intervals and ad hoc as needed to respond to requests for information, inputs to project work plans and semi-annual reports, and other internal and external data analysis and reporting requirements;
11. To take the lead in conducting continuous data analysis of enterprise/business performance from programme data and produce cross-sectional reports reflecting different growth variables including but not limited to sales, employments, profitability etc;
12. Provide analytical expertise with regards to identifying and confirming patterns and trends in data, understanding the economics of supporting different types of business, likely cost to us per unit of result, etc;
13. Provide technical assistance to Leads for implementing M&E activities, including data collection, analysis, and use of M&E systems to ensure data collected are sufficient to produce in-depth data analysis and identify trends. Ensure data are used by business units for informed decision-making and to strengthen programs/projects as needed;
14. To be the person that ultimately checks and signs off on data and analysis.

M&E work

1. Lead on designing, developing and implementing of M&E systems, including development of M&E plans, frameworks, processes and data collection tools (including baseline) for all the programmes and projects in the organization;
2. Design M&E plans and systems, identify key performance parameters for new programmes and projects and ensure the effective use by staff, partners and stakeholders as necessary;
3. Work with programmes at inception phase to define M&E plans for each project, log frames, and targets, implement the donor’s requirements, create long term plans, etc;
4. Supervise the development of appropriate monitoring, tracking and reporting systems, tools and templates that enhance monitoring of project outputs and quality, generate quality evidence on project impact and promote and ensure use of data for decision-making processes;
5. Lead regular reviews of programmes/lessons learnt sessions and implementing necessary changes to existing and future programmes;
6. Build capacity of staff in project monitoring and data collection against set indicators, and use of such information in development of project reports;
7. Develop appropriate research tools for conducting both qualitative and quantitative surveys and training staff and external enumerators in the use of the tools;
8. Support Program Managers in the formulation of baseline measures and targets, during writing and set up of project proposals as well as throughout project implementation;
9. Work closely with the communication department in developing and disseminating programme results, best practices and success stories;
10. Lead and coordinate assessment and evaluations of programmes;
11. Review the quality of existing social and economic data in the project areas, methods of collecting it and the degree to which it will provide good data for results based evaluation;
12. Report M&E updates and performances across the programmes;
13. Review or edit project data in reports as requested and required; Produce analytical summaries: graphs, charts, tables, narratives as requested, to fulfill internal and external reporting requirements;
14. Keep abreast of the latest industry developments in M&E and network with other organizations for best practices and technical assistance.

Requirements:

Experience & Qualification

• Bachelor’s degree in Statistics, Applied mathematics, Economics, Business Management, engineering or other analytics field.
• Three (3) to five (5) years of relevant professional experience doing complex data analysis within programmes M&E context.
• Proficiency with data mining, mathematics, and statistical analysis.
• Advanced experience in pattern recognition and predictive modeling.
• Experience with Excel, PowerPoint, Tableau, SQL, and basic to advanced programming languages (ex: Java/Python, R).
• Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects.
• Proven experience in leading, coordinating and managing M&E systems to produce analysis related to the economics of supporting different types of business. M&E experience within social enterprises or private sector enterprises are highly preferred.
• Strong knowledge of data quality assurance, analysis and reporting.
• Experience with monitoring and evaluation systems and frameworks for international development programs, including developing performance indicators, data collection and analysis systems and tools.
• High level of competency in managing data information.

Required Attributes:

• Very Strong analytical skills.
• Advanced excel skills are required with the ability to create excel based tools using complex formulas, pivot tables, create graphs etc.
• Highly adept with data analysis, presentation, statistics.
• Strong writing skills and experience with producing technical reports required.
• Understanding of statistical software and data management required.
• Capacity to produce high-quality briefs and reports.
• Ability to see patterns in data and understand the cause and effect.
• Excellent English writing and verbal communication skills.
• Detail-oriented and hard-working.
• Ability to collaborate well on a team while also taking initiative to complete assigned tasks with high competence.
• High level of integrity.
• Ability to communicate respectfully with multicultural clients.
• Able to work in a hybrid work environment, remotely and in person when need arises.

Preferred Attributes: 

• Interest in Data Science and Big Data Analytics
• Two or more years of project management experience
• Professional certification