World Bank Data Scientist Internship in the USA | Kickstart Your Data Science Career
The Data Lab, part of the World Bank’s DECDG and Office of the Chief Statistician, offers valuable opportunities for Data Scientist Internship to gain experience in applying modern data science to Bank operations. Interns will support the Data Corps, collaborate through the Development Data Partnership and University Data Fellows programs, and help organize workshops to build staff skills. Additionally, interns will contribute to the production of Data Goods—reproducible methods that address key challenges. As the new Data Academy is established, interns will play a role in streamlining offerings, particularly around staff certification.
Job Description
The Data Lab team seeks a talented data scientist — with experience in data engineering, data analysis and documentation, workflow management, and web development — to lead the team’s technical priorities. Following is an overview of key duties:
- Data Management System Design and Coordination. The candidate shall be responsible for oversight and periodic updating of the Development Data Partnership’s data management system design, including: ingest, pre-processing, storage, provisioning, and access management. With support from unit leadership, the candidate shall coordinate with ITS counterparts who are responsible for efficient and secure implementation of the data management system.
- Code and Data Documentation System Design and Coordination. The candidate shall be responsible for maintenance and improvement of our data and code documentation system, which shall utilize industry best practices for metadata, sustainability, efficiency, and usability. The candidate shall be supported by the team for adding content and promoting adoption of the system by Partnership members and the World Bank Data Lab community.
- Advisory. The Candidate shall, as needed and with support from the team, provide advisory on the data management system, code and data documentation systems, data, and/or data science and data engineering methods, to World Bank staff and, on occasion, to Development Data Partnership member staff.
- Data Science Analytics. The candidate shall, in coordination with team members and hired consultants, lead preparation of reusable code, methods, packages, and libraries for internal World Bank clients and/or grant-funded programs to support wider use of alternative data and data science best practices in international development.
- Product Management. The candidate, with support from the team, shall lead the design and implementation of a new front end for our GitHub-based code catalogue, making our data science methods as discoverable and valuable as our data. The candidate will also be responsible for oversight of the peer review process for ensuring certified repositories are recognized and meet the Lab’s standards for code and documentation.
- Learning. The candidate will support the team in the implementation of the data science certification program for WBG staff and in the development and delivery of learning events.
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Selection Criteria of Data Scientist Internship
- Master’s degree or equivalent qualification in the field of data science, computer science, or similar area of expertise with at least five years of relevant work experience.
- A record of high-quality and well documented data science work, using modern programming libraries and best practices;
- Ability to design complex data management pipelines for data ingest, storage, and access management;
- Ability to design and implement code and data documentation systems;
- Front-end web development experience;
- Excellent communication and interpersonal skills and ability to collaborate effectively with colleagues in a multi-cultural team;
- Ability to perform in a fast-paced environment;
- Achievement of an AWS certification preferred;
- Proficiency with the following programming languages, libraries, packages, web development resources, and platforms: python (+ NumPy, Pandas, SciPy, Jupyter, Bokeh, Seaborn, etc.), HTML, JavaScript, Hugo, Flask, git, GitHub, Docker, AWS services (S3 buckets, AWS storage options, SageMaker, etc.).
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