Data Scientist


We are a mission driven investment firm that unlocks the power of capital for sustainable growth and strong returns in underserved markets.

Job Description

CrossBoundary is recruiting a full-time Data Scientist. We are seeking candidates with proven skills in managing large data sets; applying statistics, machine learning, and other techniques to drive towards meaningful insights; and presenting these insights to varied stakeholders.

CrossBoundary is not a development firm and is not seeking typical development skills. As a Data Scientist, you will be a part of a cross-disciplinary team that has the potential to create a significant positive impact on underserved communities. You will work with data sets of vastly varying size, granularity, and quality and connect that information to concrete recommended actions. Data Scientist candidates should have at least 3 years of work experience (or applicable post-graduate education), with 1 year of experience working in high-calibre data science or consulting organizations. Experience working in developing countries will be regarded favourably.

Who We Are

The CrossBoundary team is a unique group made up of people who are genuinely excited by the opportunity to make a difference in some of the most challenging yet exciting markets in the world. Team members come from diverse backgrounds but share several qualities: curiosity, humility, integrity, a drive for excellence, and a bias for action.

Who You Are

  • A self-starter who is passionate about creating lasting change in frontier markets
  • Seeks to take on new types of work, even without prior experience/direct supervision
  • Shows willingness to work, travel, and live in a sometimes-challenging environment
  • Has comfort with ambiguity and an ability to operate effectively in a changing context
  • Can build strong relationships with clients and colleagues in stressful environments
  • Applies a “hacker mindset” towards challenges and unsolved problems

Primary Responsibilities

  • Management of data sets relevant to individual projects
  • Analysis of historical data to identify past and current patterns as well as causal relationships
  • Creation of predictive models, “What-if” scenarios, and time-series predictions
  • Design of recommendation algorithms to select optimal choices from the universe of options
  • Co-teaming with advisory and other teams and driving them to connect the data to valuable insights
  • Management of relationships with stakeholders to create trust in the project deliverables


The ideal candidate will have the following skills and qualifications:

  • 3 years of work experience (or applicable post-graduate education), with 1 year of experience working in high-calibre data science or consulting organizations
  • Experience working in developing countries will be regarded favourably
  • Expertise in at least one data-focused programming language (e.g.: Python, R, MATLAB)
  • Expertise in advanced statistical applications: non-parametric regression and classification, Bayesian methods, etc.
  • Expertise in visualization libraries (e.g.: Plotly, ggplot2, Tableau)
  • Experience in version control (e.g.: Git/GitHub) is a plus
  • Experience manipulating and transforming large data sets (e.g.: SQL, Spark, HDFS) is a plus
  • Experience in numerical optimization (e.g.: gradient-based techniques and MILP) is a plus
  • Experience with GIS tools (e.g.: ArcGIS, QGIS) is a plus
  • Ability to work independently and to learn new skills with minimal supervision
  • Excellent presentation skills; ability to communicate clearly and effectively with diverse audiences

About the Firm

Founded in 2011, CrossBoundary is a mission-driven investment firm committed to unlocking the power of capital to make a substantial return while creating a lasting difference in underserved markets. CrossBoundary provides investment advisory services, having developed specialized expertise in unleashing investment across all sectors in these markets. Our advisory clients include governments, development finance institutions, private equity firms, Fortune 100 companies, and research institutions. Learn more at

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