Data Analytics Fellow
Babban Gona Farmer Services
About the organization
Babban Gona (“Great Farm”) is a rapidly scaling social enterprise, with a mission to serve the bottom of the pyramid and transform agriculture into a job creation engine for unemployed youth. We do this by offering a suite of services to rural, smallholder farmers, helping them to overcome the challenges of fragmentation and low economies of scale. Our services include providing financial credit, low-cost high quality inputs, ongoing training on best agronomy practices, and providing storage and marketing services to maximize farmers’ profits. In 8 years, BG has helped over 65,000 smallholder farmers increase their productivity by 2x the national average and profitability by 2.5x to 3x the national average. Our goal is to serve 1,000,000 smallholder farmers in 2025.
We work with low income small holder farmers that are often outside the formal economy. There is limited to no data on these groups in most standard data repositories e.g. demographic data, addresses, asset ownership /land title information; even telephone history is often non-existent. Consequently, it is extremely difficult for potential investors /entrepreneurs /partners to make smart, data-driven business decisions when working in these areas. Fortunately, over the last several years of operations, Babban Gona has collected a significant amount of data on our farmer members. We have deep roots in these communities and we know the farmers intimately well.
Our Data Analytics Fellow will work across the business to convert our data bank to useful insights. Key responsibilities include, but are not limited to:
● Track business performance in real-time using data visualization tools such as Tableau.
● Review and analyze large data sets from multiple internal and external sources.
● Conduct data extraction, consolidation, preparation, analysis and presentation of results.
● Perform correlations, regressions and other analysis that provides key business insights
● Conduct predictive forecasts that improve business decision making.
● Ability to design, implement and iterate machine learning models from prototypes to production will be fantastic.
● Bachelor’s degree in Mathematics, Computer Science, Data Science, Statistics, Engineering or any other related field.
● At least 2 years’ experience in data analytics, business intelligence or data science.
● Proficiency in real-time data visualization tools preferably Tableau.
● Proficiency in SQL, Excel and one or more statistical tools like R, SAS, VBA, SPSS. Familiarity with statistical techniques such as predictive modeling, regression, cluster analysis, factor analysis, multivariate statistics and neural networks. etc.
● Obsessive attention to detail, positive attitude and a constant willingness to learn.
● Passionate, driven individual with an ability to achieve results through teamwork and collaborative approaches.
$1250 per month
Contact email: [email protected]
We welcome applications to our Fellows Program on a rolling basis and will match candidate skills and interests with business requirements. Applications will be processed and candidates interviewed as new opportunities emerge. While individual preferences are taken into account, offers to join the Babban Gona Fellows Program are subject to project needs at the time of application.
To apply, please send your CV and a brief cover letter expressing how your background has prepared you to make significant contributions as a BG Fellow with subject line: BG Fellows Program [Data Analytics].
Equal Opportunity Employment
The posting employer has certified that this announcement complies with Peace Corps’ Equal Opportunity Employment policy:
The Peace Corps is committed to providing equal opportunity to all employees, Volunteers, and applicants for employment and volunteer service. Peace Corps policy prohibits discrimination and harassment because of race, color, religion, sex, national origin, age (40 or over), disability, sexual orientation, gender identity, gender expression, marital status, parental status, political affiliation, union membership, genetic information, or history of participation in the Equal Employment Opportunity process, grievance procedure, or any authorized complaint procedure.
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