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Industry (Information technology, software development, data)
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Seniority (Information technology, software development, data)
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Innovations for Poverty Action (IPA)
Non-profit + 1 more
Description
Qualifications
- Bachelor's degree or equivalent in computer science, data science, statistics, economics, social sciences, or a related quantitative discipline.
- At least three years of professional experience in data science, data engineering, research support, or a related field, with a demonstrated record of owning and delivering technical projects independently. (Data Scientist I candidates: at least two years of relevant experience with demonstrated ability to manage analytical tasks with limited supervision.)
- Proven experience developing data science or data engineering projects in Python.
- Proficiency in SQL for database querying and analytics.
- Experience with version control systems such as Git, and with reproducible, well-documented workflows.
- Strong quantitative skills and a solid understanding of core statistical concepts, including regression, hypothesis testing, and sampling.
- Demonstrated ability to clean, manage, analyze, and document data.
- Clear written and verbal communication in English, with the ability to document, explain, and present technical work.
- Ability to build effective working relationships in a multicultural environment with sensitivity and respect for diversity.
- At Data Scientist II level: proactive communication, surfacing progress, risks, and decisions without being asked, and experience mentoring or serving as a technical reference for peers.
- Experience with cloud computing platforms (AWS, GCP, or Azure) and analytics databases (Snowflake, Databricks, Redshift, MotherDuck, or ClickHouse). (preferred)
- Background in applied machine learning, natural language processing, and large language models. (preferred)
- Working knowledge of Stata and SurveyCTO for research support, and of additional analytical software such as R. (preferred)
- Experience with data engineering tools for ELT workflows such as dlt, SQLMesh, or dbt. (preferred)
- Experience with geospatial analysis. (preferred)
- Familiarity with research quality standards and best practices in survey data collection and data management. (preferred)
- Experience with project management tools such as Jira or Asana. (preferred)
- Experience working with international development organizations or research institutions. (preferred)
- Ability to work in one or more of the following languages: Spanish, French, or Swahili. (preferred)
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