Women’s World Banking is the global leader in women’s financial inclusion. Rooted in its deep understanding of the women’s market, Women’s World Banking tackles financial inclusion in three interconnected ways: first, by partnering with financial services providers to develop scalable market-driven solutions; second, through its gender-lens private equity fund; and, finally, because diverse institutions are proven to be stronger, Women’s World Banking builds institutional capacity through leadership and diversity programs. Through this holistic approach and the organization’s global reach of 49 institutions in 32 countries, Women’s World Banking accelerates economic opportunity for low-income women and growth for financial service providers in the emerging markets.
About the Job:
The Data Analyst will work directly with internal and external stakeholders as well as data providers, leveraging advanced statistical techniques to drive strategic thought and effective decision making in addition to collect and analyzing data an information about customers, markets and the business environment in countries in Africa, Asia, and Latin America.
The Analyst also supports all aspects of analytic initiatives from conception to completion, through the development of clear and well-structured analytical plans, and ability to analyze large and complex data-sets. This role will serve in shaping Women’s World Banking business’s data infrastructure, inclusive of data-warehousing, reporting, modeling, and analytics platforms, as well as supporting a variety of data insights and data reporting needs, including, but not limited to, customer segmentation analysis and look-alike modeling, use case development and validation, cross-country trend analysis, and data visualization.
Tasks and Responsibilities:
Serve as primary resource for supporting measurement and data analysis needs including: integration of multiple large datasets for ongoing data analysis and mining; data cleaning and variable development; quality control; data segmentation design; programming and analysis. Build and manage large and complex (multi-source and multi-stream) datasets with internal platforms and resources.
Work with research team to support Women’s World Banking project objectives and develop datasets and analysis that provide the most accurate and comprehensive picture.
Serve as key team member in development of predictive analytics methodologies and models for use in ongoing applied research projects.
Develop and implement analytical strategies through a range of quantitative research methods to provide data driven insights that support iterative development of the research project.
Work as a member of the research team to recommend the best analytic approaches and set the standard of excellence for conducting, packaging, and reporting on frequently used analyses and datasets.
Conduct a range of statistical tests on datasets to understand aspects of client and organization patterns and relationships including descriptive statistics, segmentation analysis of patterns and trends, inferential statistics and experimental and quasi-experimental tests of difference and relationships.
Assess the methodologies, data quality and synergies across various third-party data sets and develop strategic recommendations on behalf of the research team.
Demonstrated ability to “tell the story” with data at the executive, manager, and team levels using charts and other data visualizations that are clear and easy to understand for any interested layperson.
Bachelor’s degree in Statistics, Applied Statistics, Mathematics, or a quantitative field with concentration in mathematics, economics, or social science required; Excellent understanding of both the business and non-profit worlds and the research required in each of them.
This hands-on applied role will require between three to five years of professional experience with an aptitude for collaboration, as well as a detail-oriented mind-set coupled with the ability to define and shape research agendas.
Strong analytical skills including reporting, building dashboards, segmentation, trends analysis, predictive modeling, inferential and regression analysis.
Strong experience with data manipulation and visualization tools including: SAS, SQL, Tableau, SPSS, STATA.
Data cleaning (including missing values and analyzing patterns to detect incomplete data), integration and merging, variable construction and database management with one-time and continuous building of datasets.
Experience with different types of data sets including, but not limited to, surveys (both small and large including publicly available datasets), public administrative data and proprietary administrative data spanning multiple time frames.
Working with algorithms (including R, python) and applying new and innovative ways of solving data problems with innovative solutions. Querying experience in large datasets.
Training and applied experience in infographic design and integration into data analysis and interpretation.
Willingness to travel to emerging markets.
Familiarity with experimental design methodologies.
Strong segmentation skills (demographic, behavioral and LCA).
IRB CITI certification and experience with IRB protocols and applications.
Experience requesting and translating needs of research questions to various types of IT systems and reporting functions (some experience with SQL, Java or other reporting systems a plus).
Interest in the field of financial inclusion, including gender.