Application Deadline! Applications for this post are now closed
One Acre Fund is seeking a Data Scientist to leverage our central data warehouse to drive core business functions like repayment collection, client enrollment and retention, product adoption, and supply chain optimization. A successful candidate in this role will be a pro-active and independent worker able to manage numerous internal and external relationships, scope and organize project needs, and communicate effectively with stakeholders along the full spectrum of data fluency. S/he will build relationships and learn 1AF operations to utilize the appropriate local context to design scalable and accessible decision support tools. The role will also support internal agronomic research efforts and provide support for using data to improve decision making across the organization.
- Improving accuracy and efficiency of core business functions - One Acre Fund collects information on what clients purchase, payment behavior, and client retention over seasons. A successful data scientist will leverage these data to build predictive models to support business decisions such as, “how do we proactively seek out defaulters?” and “how can we tailor our product marketing most effectively?” Success will be measured by empowering country programs to reach impact and scale targets with greater efficiency.
- Exploration – The Business Intelligence team manages the organization’s core data reporting system; we are tasked with identifying new impact opportunities for country research teams (Innovation Teams and field teams ) to assess and scale. A successful Data Scientist will deeply understand the ins and outs of the field program so s/he can propose new global research programs, change the way that we approach existing analyses, and identify new avenues by which One Acre Fund can deliver data-driven impact to smallholder farmers.
- Adapting agronomic elements of the program to heterogeneous conditions – The Data Scientist will be responsible for working with internal and external agricultural scientists to analyze field crop yield gap drivers and develop agronomic hypotheses to be tested through on-farm trials. This will involve aggregation of weather, soil, pest and disease, and agronomic data to analyze the magnitude of various sources of yield variation in different areas of program operation. It will also involve coordinating with field teams to collect the data we need and setting and executing analysis plans.
- Capacity building and advising – We are looking for someone with experience and willingness to teach others and advise on organizational data and analytical decisions. A successful Data Scientist will enable and improve the analyses of other analysts both within the Business Intelligence Team, Agricultural Research Team, and in other departments. The data scientist will seek to use their experience and influence as an organizational data leader to affect how the organization at large utilizes data for decision making. Support topics may include questionnaire design and execution, efficient data cleaning, outlier management, model selection and interpretation, and predictive analyses.
CAREER GROWTH AND DEVELOPMENT
We have a strong culture of constant learning and we invest in developing our people. You’ll have weekly check-ins with your manager, access to mentorship and training programs, and regular feedback on your performance. We hold career reviews every six months, and set aside time to discuss your aspirations and career goals. You’ll have the opportunity to shape a growing organization and build a rewarding long-term career.
We are seeking an exceptional professional with 3+ years of experience, a demonstrated passion for development work, and a very strong knowledge of analysis and data science. Candidates who fit the following criteria are strongly encouraged to apply:
- MSc or PhD in a highly quantitative field such as data science, statistics, econometrics, computer science, or applied mathematics required.
- Knowledgeable in predictive and causal analyses in Python and R including:
- Knowledge and experience in supervised and unsupervised machine learning techniques: statistical tests, regression, Random Forest, Boosting, PLS, DNN, K-means clustering, etc.
- Experience querying databases with SQL.
- Experience visualizing/presenting data using ggplot, matplotlib, or seaborn.
- Experience with field experiments and experimental design preferred. A successful candidate will understand how to derive causal estimates from structured experiments as well as other causal inference methods (e.g. regression adjustment, propensity score stratification), or quasi-experimental methods (e.g., instrumental variables, regression discontinuity, interrupted time series) and the appropriate statistical methods.
- Strong, independent self-starter with an emphasis on delivering results and communicating proactively with management and collaborators.
- Excellent written and verbal communication skills for coordinating across teams.
- Experience and comfort with geospatial analysis preferred.
- Professional or research experience in agriculture and/or development preferred. Interest in learning more about needs of smallholder farmers a must.
- Fluency in English required, Kiswahili and/or French a plus.
- A willingness to live and work in East Africa for at least two years.
PREFERRED START DATE
Commensurate with experience.
Health insurance, housing, annual flights and other quality of life benefits.
SPONSOR INTERNATIONAL CANDIDATES
Yes. East Africans are strongly encouraged to apply.