Description:CrossBoundary is a mission driven investment firm committed to unlocking the power of capital to make a strong return while creating a lasting difference in frontier markets. We take a transaction centered approach to frontier markets. CrossBoundary provides investment advisory services, having deve…CrossBoundary is a mission driven investment firm committed to unlocking the power of capital to make a strong return while creating a lasting difference in frontier markets. We take a transaction centered approach to frontier markets. CrossBoundary provides investment advisory services, having developed a specialized expertise in unlocking investment across all sectors in fragile and frontier markets. Our advisory clients include governments, development finance institutions, private equity firms, Fortune 100 companies, and research institutions. Our direct investment arm, CrossBoundary Energy, finances solar projects in Africa.View moreView less
Clean, structure, and analyze large datasets (e.g., smart meter data, site-level operational data, revenue data exports)
Develop Python scripts to automate recurring data cleaning and aggregation workflows
Conduct time-series analysis to assess site performance (e.g., consumption growth, uptime, load profiles, revenue trends)
Support cross-site performance comparisons and prototype impact assessments
Identify anomalies, trends, and patterns in operational data
Develop visualizations and dashboards to communicate findings clearly
Support the preparation of data-driven insights for donor reports, internal memos, and sector publications
Contribute to strengthening the Lab’s internal data infrastructure and analytical tools
Required Technical Skills:
Python (Intermediate to Advanced)
Strong experience with Pandas (data cleaning, merging, grouping, aggregations)
Experience with NumPy (numerical computations and array operations)
Experience handling and analyzing large CSV datasets
Experience conducting time-series data analysis (resampling, rolling averages, trend analysis)
Strong data cleaning skills
Proficiency in Excel (formulas, structured sheets)
Basic data visualization skills (Matplotlib / Plotly or similar)
Who you are
Self-starter who is passionate about creating lasting change in underserved markets
Takes on new types of work, even without prior experience/direct supervision
Passionate about using data to improve energy access and climate solutions
Highly analytical and detail-oriented
Comfortable working with messy, real-world datasets
Able to operate independently and manage structured deliverables
Able to communicate technical findings clearly and succinctly
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