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Day 21
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Learning Data Analyst
Reads like a Data Scientist role: models and experiments.
EIDU e.V.
Live, first seen by us 21 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Permanent — employment source
Employment type in the employer’s posting: Permanent employee
From the employer’s posting
What you’ll work on
Full postingWe are looking for a Learning Data Analyst to form an integral part of the Impact team.
We regularly test changes to our product and programme through experiments.
Link app usage, dosage, coverage and progression to learning outcomes
Diagnose where the programme works and recommend the next change
Plan, design and analyse experiments end-to-end, including power calculations
Run funnel, cohort and fidelity analyses to find what to test next
Partner with the Ops/BI Analyst on dashboards and routine reporting
From the employer’s posting
We are looking for a Learning Data Analyst to form an integral part of the Impact team. You will own one question: What in our learner and teacher data is driving learning outcomes and where can we head next? You will use data to identify where the programme is working and where it isn't, and what that implies for the next change we should make.
We regularly test changes to our product and programme through experiments. You will help design these tests from the start, using your statistical knowledge to choose the right method and work out the population and sampling approach. When the results come in, you will analyse them and explain clearly what worked and what didn’t. Between experiments, you will explore our data to find patterns that point to what we should test next.
Link what learners and teachers do in the app, how much they use it (dosage), how many are reached (coverage) and progression related to learning outcomes.
Diagnose where the programme is working and where it isn't, and translate findings into clear recommendations for the next product or programme change.
Plan, design and analyse experiments end-to-end: randomisation design, power calculations, and standard causal analyses of results.
Between experiments, run the discovery engine — funnel, cohort and fidelity analyses — to surface the next thing to test.
Partner with our Ops/BI Analyst on shared surfaces such as dashboards and routine reporting..
About EIDU e.V.
We believe every child deserves the chance to reach their full potential — and that strong foundations in literacy and numeracy are where this begins.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 13, 202621 days ago
- Recorded sightings
- 20
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EIDU e.V. is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- dbt
- Metabase
- Redshift
Where the posting names them
What you should bring: - Strong SQL and Python, with experience working directly against large, messy event-level datasets. - Practitioner-level statistics: comfortable with experimental design, power analysis, and standard causal inference methods.
- Work with the operations and learning teams to frame the right analytical questions, grounded in learning-science literacy. - Work directly with our tech stack: Redshift, Metabase, dbt What you should bring:
Your next step
Complete your application on eidu.jobs.personio.de. The employer’s form will show what is required.
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- No account needed. The 20 MB limit covers all your files together, not each one.
Already applied? Track this application
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About Us
About the role
What you will do:
What you should bring:
This is right for you if
This probably isn't for you if
Our Stack
What we offer:
We believe every child deserves the chance to reach their full potential — and that strong foundations in literacy and numeracy are where this begins.
EIDU partners with governments to strengthen public education systems at scale. Our technology-enabled platform integrates proven educational interventions and supports learners, teachers, education officers, and ministry staff within national systems.
Today, we work with 41 governments and will reach 1,000,000 active students across Kenya and Nigeria in 2026. We have doubled our learner numbers each year over the last five years and aim to reach tens of millions more. A randomized controlled trial found a 0.53 standard deviation improvement in learning outcomes — placing EIDU among the top 10% of education interventions in low- and middle-income countries.
We combine analytical rigor, entrepreneurial drive, and disciplined execution. As we scale, we are building an organization capable of turning strategy into measurable impact at national scale.
About the role
We are looking for a Learning Data Analyst to form an integral part of the Impact team. You will own one question: What in our learner and teacher data is driving learning outcomes and where can we head next? You will use data to identify where the programme is working and where it isn't, and what that implies for the next change we should make.
We regularly test changes to our product and programme through experiments. You will help design these tests from the start, using your statistical knowledge to choose the right method and work out the population and sampling approach. When the results come in, you will analyse them and explain clearly what worked and what didn’t. Between experiments, you will explore our data to find patterns that point to what we should test next.
[Location: Kenya/Nigeria/Germany/India preferred, open to discuss]
What you will do:
- Link what learners and teachers do in the app, how much they use it (dosage), how many are reached (coverage) and progression related to learning outcomes.
- Diagnose where the programme is working and where it isn't, and translate findings into clear recommendations for the next product or programme change.
- Plan, design and analyse experiments end-to-end: randomisation design, power calculations, and standard causal analyses of results.
- Between experiments, run the discovery engine — funnel, cohort and fidelity analyses — to surface the next thing to test.
- Partner with our Ops/BI Analyst on shared surfaces such as dashboards and routine reporting..
- Work with the operations and learning teams to frame the right analytical questions, grounded in learning-science literacy.
- Work directly with our tech stack: Redshift, Metabase, dbt
What you should bring:
- Strong SQL and Python, with experience working directly against large, messy event-level datasets.
- Practitioner-level statistics: comfortable with experimental design, power analysis, and standard causal inference methods.
- A track record of turning ambiguous event data into clear, decision-useful analysis.
- Enough learning-science literacy to ask the right questions of learner and teacher data — formal background or applied familiarity both welcome.
- Comfort operating between rigorous experiment analysis and open-ended discovery work, and communicating both clearly to non-technical stakeholders.
- Excellent communication skills, including the ability to communicate effectively in a multi-cultural environment and communicating technical information with non-technical audiences.
This is right for you if
This probably isn't for you if
- You want to build production ML models or data pipelines.
- You want to own dashboards and regular reporting only.
- You need clean, well-documented data before you can start.
- You want a large analytics team around you.
Our Stack
What we offer:
- Work on one of the biggest problems in the world: ensuring every child gets the education they deserve.
- Being a part of an international and passionate team located in Kenya, Germany and Nigeria.
- An open environment where feedback is welcomed, promoting mutual growth.
- High degree of flexibility with regard to working hours and vacations.
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
EIDU e.V.
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.