Full Stack Data Scientist III/IV

Role Overview

As a senior data scientist on our team, you will take on the technical lead role for multiple projects aimed at solving pressing social problems in global development. Your days will be split between designing data-driven solutions with clients, writing production-ready Python code, guiding junior colleagues, and shaping what responsible AI looks like in our sector. Your work directly determines whether the tools we deploy actually improve the lives of disadvantaged populations.

Key Responsibilities

• Lead end-to-end delivery of data science projects, from initial client conversations through deployment, acting as both the technical architect and an individual contributor who writes production code.
• Translate messy, real-world client challenges into tractable data science questions—and push back when a sophisticated model is not the right answer given the resources or context.
• Build and deploy complete solutions, including APIs, user interfaces, automation pipelines, and monitoring systems, ensuring they are robust enough for use in low-resource and unpredictable field settings.
• Establish and enforce engineering and data science standards on the team, including code review practices, documentation quality, and structured evaluation of model performance.
• Coach and mentor junior data scientists, giving targeted feedback on both technical execution and communication so they can grow into independent contributors.
• Serve as the recognized internal expert in one or more specialties—such as machine learning, LLMs/GenAI, optimization, geospatial analytics, or MLOps—and guide method selection across projects.
• Identify emerging trends and gaps in the AI-for-good landscape, propose new service offerings or internal tools, and contribute to thought leadership on ethical and effective deployment of data science.
• Maintain your own professional development plan with support from leadership, actively seeking stretch assignments and incorporating regular feedback to deepen your expertise.

Requirements & Qualifications

• Master’s degree plus 8 years of hands-on experience as a data scientist using Python, or a PhD plus 4 years of equivalent applied experience.
• Deep expertise in at least one data science specialty, such as predictive modeling, deep learning, GenAI/LLMs, NLP, optimization, or geospatial analytics, demonstrated through shipped projects.
• Strong Python fundamentals, including experience working with and maintaining complex codebases in a production environment.
• Working knowledge of at least one adjacent engineering discipline: AI engineering, MLOps, backend development, DevOps, or frontend development.
• Broad familiarity with advanced machine learning and statistical methods, including solid foundations in probability and statistics.
• Proven experience leading technical teams to deliver complex data science or AI solutions, including mentoring and knowledge-sharing.
• Comfort with collaborative software development practices, including version control and peer code review.
• Ability to work independently and adapt quickly in a dynamic, multicultural environment, often tackling problems that are new, unusual, or poorly defined.
• Excellent written and spoken English; professional working proficiency in French is a plus.
• A genuine commitment to global development and improving outcomes for disadvantaged communities.

What We Offer / Why Join

This role offers the opportunity to take full ownership of high-impact technical projects and set the standard for engineering rigor in a mission-driven organization. You will receive regular real-time feedback and structured performance reviews, alongside access to stretch roles designed to accelerate your professional growth. The culture is intentionally entrepreneurial, meaning you can shape your career path—whether you want to deepen your technical skills, move into management, or grow into a client-facing leadership position—while working alongside colleagues who share your passion for using data to improve lives.