Operation Research Lead Analyst
- Deadline for Applications
- Contact Information
Sanergy is an award-winning social venture that builds healthy, prosperous communities by making hygienic sanitation accessible and affordable in Africa’s urban informal settlements. Our systems-based approach to solving the sanitation crisis involves five key steps: we build a dense network of franchised micro-entrepreneurs, who operate low-cost, high-quality waterless sanitation facilities – called Fresh Life – as small businesses. We provide critical support services – such as access to finance, business analytics, training, and marketing. We collect the waste regularly and safely remove it from the community. We convert the waste into valuable by-products, such as organic fertilizer and renewable energy. Finally, we sell the by-products to Kenyan farms.
We launched our first toilet in November 2011, and we now have a network of over 600 active Fresh Life Toilets run by over 300 Fresh Life Operators. We have collected and converted over 8,000 tons of waste. At the same time, we have built a team of over 250 people. For our work, we have been recognized by Fast Company as one of the 10 Most Innovative Companies in the World Doing Social Good and one of the 10 Best Companies in Africa.
More qualitatively, we are looking for people who have the desire to take on a new challenge in a pioneering context. We believe that we are on the cusp of transformative change and we seek people who believe their knowledge and skills will bring about that change.
The Operation Research Lead Analyst will lead the Operational Research team at Sanergy. In partnership with the operations team, the successful candidate will focus on three major areas: providing analytical support to operational teams, management of user, customer and market research activities and, capacity development of colleagues and junior analysts.
The major focus of the role will to be to develop an operational management platform that informs decision-making across the organization. This will require close collaboration with front line staff up to directors and will enable the candidate to gain full exposure to the workings of the organization.
In addition, the candidate should have the capability to design qualitative and quantitative research projects.
For example, modeling the purchasing behavior of our main customers and to develop key profiles of our target markets the second focus is on contributing to growth strategies through monitoring and evaluation of operations and strategies. The last area is around building the capacity of team members and colleagues throughout the organization to conduct high quality research.
Role & Responsibilities
- Responsible for generating business intelligence that supports teams when they are making decisions
- Responsible for coaching junior staff how to use data to make evidence based decisions
- Responsible for influencing senior management on how to use data to make evidence based decisions
- Transform traditional hierarchical Data Warehouse into Data Discovery agile analytics by leveraging mobile technology and reporting platforms
- Responsible for project management activities including project scoping and problem definition, gaining buy-in from key stakeholders, timeline planning and resource planning,
Provide support to colleagues to conduct high quality quantitative and qualitative research
- Build skills of other researchers
- Managing a team of researchers
Education & Experience
- Proven ability to generate insights that directly influence operational activities
- Master’s degree (or equivalent work experience) in a pure or applied numeric discipline (e.g. mathematics, economics, political science, psychology, engineering)
- Proven experience with qualitative and quantitative research design
- Proven experience with collection, transformation, quality checking and modeling datasets.
- Proven experience defining, communicating and executing to a strategy in high-performance oriented business environment
- In-depth understanding of data discovery, analytics, operational reporting, data warehousing and data quality
- Advanced knowledge of statistical techniques including multivariate regression, GLM, factor analysis
- A process focused mindset – the ability to think about the process of data collection and end use rather than a focus on building tools
- Ability to use statistical packages such as SPSS or Stata
- Ability to use programming language and programming software such as SQL
- Ability to present data in charts, graphs, tables and reports
- Ability to train colleagues on the use and application of advanced analytical methods