The Rockefeller Foundation’s Data and Technology team is seeking an experienced Full Stack Data Scientist to join its growing data analytics unit.
Your main responsibility will be working closely with colleagues across the organization to develop analytical products and solutions to solve their business needs, and to help the Foundation use data science to achieve social impact.
The Rockefeller Foundation’s mission is to promote the well-being of humanity throughout the world. We use data and technology to amplify the impact of our work. For example, to fill gaps in the availability of timely agricultural data in Africa we’ve invested in a data science startup which is integrating data from satellites and surveys and using sophisticated AI techniques to predict crop yields at high resolution. Similarly, our power team is using novel data sources and machine learning approaches to estimate demand for energy across low and middle-income countries. Developing effective APIs, data visualizations and analyses on top of this work will give energy planners and investors the insights they need to deploy the right energy infrastructure to bring electricity to the unconnected.
Creativity, collaboration and analytical thinking will be central to this role. You should have a breadth of computational and statistical tools and techniques at your disposal, and have experience running a variety of successful data science projects which solve a problem, while building the team’s capability to tackle the next one.
Above all, you’ll have a passion for working with others to solve problems with data and have the skills to excel in an organization with over 100 years of experience putting data at the heat of its work.
Principal Duties and Responsibilities
You will be part of the Rockefeller Foundation’s Analytics Team and the organization’s Data Science Community of Practice. Your main responsibilities will include:
- Full stack data science: You’ll spend around 50% of your time working with experts and grantees from the Rockefeller Foundation’s initiative areas and operations teams to develop analytical products which meet their needs. From design and discovery to the deployment and maintenance of solutions, you’ll use a variety of AI, machine learning and statistical techniques to analyze structured and unstructured data; develop and apply new and existing models and algorithms; and produce well documented, reproducible work that is communicated clearly.
- Infrastructure and policy: You’ll spend around 30% of your time building out the Foundation’s data science infrastructure including growing our library of data assets and establishing good data management practices; designing and rolling out internal data policies; and building and maintaining cloud and local infrastructure for development and production use, in close collaboration with our IT department.
- Creative and strategic exploration: You’ll cultivate and identify opportunities for how your data science skills and the Foundation’s growing data assets and partnerships can be used to advance our mission.
- Ethics and accountability: You’ll champion the responsible use of data science across the Foundation’s initiatives, and bring a practical understanding of fairness, accountability, transparency and ethics to the analyses you produce and products you help to build.
Education, Experience and Skills
A masters in a quantitative discipline and at least 5 years of professional experience working as a full stack data scientist in an institutional setting such as a consulting firm, technology company or research organization.
Qualifications and Competencies
- Statistics and machine learning: A deep, practical understanding of statistics and the ability to apply a variety of statistical concepts and machine learning techniques to real world analytical problems, understanding their advantages and drawbacks.
- Statistical computing: Fluency in R and/or Python. Able to use software engineering best practices to develop well-documented and engineered analyses which are reproducible and maintainable. Comfortable working with a variety of data types from unstructured text, images and video to surveys, time series statistics and large high-resolution sensor data. Good geospatial analysis and visualization skills are essential.
- Systems engineering: Comfortable setting up and using cloud computing tools and working with IT teams to develop policies and infrastructure to support data science across the institution.
- Project and client management: Experience managing a variety of data science projects from conception to completion. The ability to prioritize, iterate and deliver valuable results quickly. Able to work with minimum supervision and demonstrate good analytical judgement, business sense, and client relationship management.
- Communications, writing and training: Demonstrated ability to write well and communicate clearly. Able to effectively share knowledge and train others to develop their data literacy skills and understanding of the data science process. A proven ability to learn continuously and independently in order to keep skills at the forefront of current practice.
The Rockefeller Foundation is committed to the principles of equal employment opportunity and to compliance with all federal, state, and local laws concerning employment discrimination, including the Americans with Disabilities Act. To this end, the Foundation ensures equal opportunity to all employees and applicants regardless of race, color, age, gender, sexual orientation, religion, marital status, national origin or ancestry, citizenship, lawful alien status, physical, mental, and medical disability, veteran status or liability for service in the United States Armed Forces.
The Rockefeller Foundation is an Equal Opportunity Employer[ssba]