Full Stack Data Scientist III/IV

***Location: Rabat, Morocco (preferred) or Dakar, Senegal (preferred); open to other IDinsight office locations (Nairobi, Kenya; New Delhi, India; Manila, Philippines; Lusaka, Zambia)***

IDinsight is hiring full-time senior data scientists (4 to 8 years of relevant experience) to grow our machine learning, AI, and broader data science capabilities. In this role, the data scientist will leverage their expertise to drive social impact across multiple project teams and clients. You may lead work on models that help locate out-of-school children, LLM-powered co-pilots for teachers, agentic systems that help citizens access benefits, geospatial tools for planning public infrastructure, or optimization models for allocating resources in public health. We are a social-impact-oriented organization, so we can guarantee incredibly meaningful work tackling some of the world's most complex international development challenges.

**Build cool stuff. Have a positive impact.**

We are working to build IDinsight into a global leader in the use of data science, ML, and GenAI to solve some of the world's most urgent problems. As an expert in the field, you will provide guidance on methods, tools, design, and deployment of the solutions we build.

You'll be joining a growing data science team and working on highly impactful and innovative projects with our partners. We are an entrepreneurial team where you have a strong voice in how the team functions and grows.

You'll get to work on the full spectrum of a solution- from design to deployment. This includes not just data processing and algorithm design, but also full-stack engineering work. You may also evaluate tools that other organizations in the sector are building, and provide critical input for improving or scaling them.

Data science products need to be contextually relevant and build on subject-matter expertise to be effective. You will work closely with our partners and a multidisciplinary team- including economists, social sector experts, and domain experts (public health specialists, education experts, government officials)- to build and test solutions.

Learning is a key part of being a data scientist. 10% of your time would be dedicated to learning new skills and side projects of your choice. You'll have strong mentorship to guide your career, and you'll make interesting and valuable connections.

**About IDinsight**

IDinsight helps leaders combat poverty worldwide by designing, deploying and promoting evidence-generating tools. We tailor the best methodologies to partner needs and constraints to fuse evidence with action. We serve governments, NGOs, foundations and social businesses across Africa and Asia in all major program areas, including health, education, agriculture, livelihoods, finance, energy and governance.

Our approach rests on four pillars:

- Rigorous: We develop and use a wide range of cutting-edge data and evidence tools, including experimental evaluations, monitoring systems, data analytics and visualization, process evaluations, machine learning and more.
- Cost-effective: Every dollar spent is justified by expected impact. If funds could be better used in another way, we say so.
- Timely: Actionable information is delivered in time for client decision-making deadlines.
- Demand-driven: We deploy solutions tailored to partner contexts and needs with no competing agendas.

Our diverse, growing team of roughly 200 outstanding colleagues operates in nearly two dozen countries worldwide. Learn more about our mission and values at[ www.IDinsight.org](http://www.idinsight.org/).

**About the Role**

We are seeking candidates with a strong background in Python, deep applied expertise in one or more data science specialties (e.g., machine learning, LLMs/GenAI, optimization, geospatial analytics, MLOps, or full-stack engineering for data products), experience building and deploying solutions in production, and a passion for building solutions to difficult social problems. Most importantly, successful candidates should have the ability to learn and adapt quickly, and work independently to solve complex human and technological challenges.

As a senior data scientist, you'll lead multiple projects as tech lead and be responsible for the performance of the solutions. Day-to-day work may include:

- Working with clients to understand their needs: Understanding their current processes and pain points, identifying which of these can be framed as tractable data science problems, and knowing when they can't, and even when it is, the solution must suit the task and resources available.
- Leading solution design and delivery end-to-end: Rolling up your sleeves as an individual contributor- writing production code, designing and evaluating methods and models, and building and deploying solutions (including APIs, UIs, CI/CD, etc.); while also working alongside other data scientists to shape the overall approach, synthesize findings, and communicate results.
- Establishing standards and best practices: Bringing experience in writing quality code, conducting code reviews, and providing feedback on technical and non-technical documentation. Setting the bar for engineering rigor and project management on the team.
- Coaching and mentoring: Upskilling junior data scientists on methods and approaches, and providing structured feedback on both technical and delivery skills.
- Providing thought leadership in your specialty: Leading the org through deep expertise in a subset of the following (machine learning, deep learning, GenAI/LLMs, NLP, optimization, geospatial analytics, backend development, frontend development, DevOps, or MLOps) — and drawing on broad familiarity across methods to make sound judgment calls on which approach fits which problem.
- Shaping the sector: Identifying trends and gaps in the AI-for-Good space; proposing products or services that could address these gaps; and contributing thought leadership on how data science and AI can be deployed responsibly and for the right problem types.

Moreover, professional development for our technical roles is essential for IDinsight’s long-term impact. With support from IDinsight leadership, the employee will maintain self-directed professional development plans and will be given "stretch" opportunities designed to strengthen their professional skills. Real-time feedback and structured reviews are regularly provided to maximize each data scientist’s expertise. IDinsight’s entrepreneurial culture allows roles and career progression to be tailored to individual strengths, interests, and goals. Employees have the opportunity to increase responsibilities, and high performers will have the opportunity to move up in the organization along technical, managerial, or client-facing paths.

**Required Technical Qualifications**

- Master's degree and 8 years of experience, or a PhD and 4 years of experience, as a data scientist working in Python.
- Demonstrated expertise in a subset of the following data science specialties: predictive modelling, machine learning, deep learning, GenAI/LLMs, NLP, optimization, or geospatial analytics.
- Intermediate-to-advanced Python skills / experience working on complex codebases.
- Working knowledge of at least one of: AI engineering, MLOps, backend development, DevOps, and frontend development
- Broad knowledge of advanced machine learning and data science methods.
- Strong foundations in statistics and probability.
- Proficiency in collaborative software development practices such as version control and code reviews

**Other required qualifications:**

- Proven ability to work independently and with teams in a dynamic, multicultural environment.
- Experience leading technical teams to deliver complex data science or AI solutions, with a strong interest in mentoring, knowledge-sharing, presenting work and providing feedback to others.
- Strong oral and written communication skills in English. Professional proficiency in French