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Day 156
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Learning Data Analyst
Karachi, Pakistan
Open 5 months, first seen by us 156 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingSupport the implementation of predictive models for student progress, attendance, and learning risk levels.
Support the generation and refinement of the School Health Index (SHI), a dynamic bench-marking tool that compares school- and region-level performance.
Analyze outputs from machine learning models built in collaboration between TTWF and MIT (using Python-based tools).
From the employer’s posting
Operate and maintain the Learning Dashboard, which merges backend data from TTWF and in-app platforms Support the implementation of predictive models for student progress, attendance, and learning risk levels. Generate weekly insight reports for internal teams to identify schools or students needing intervention.
3. School Health Index (SHI) Analytics Support the generation and refinement of the School Health Index (SHI), a dynamic bench-marking tool that compares school- and region-level performance. Help ensure SHI accuracy through validation with field data and stakeholder input.
4. Predictive Modeling & Advanced Analysis Analyze outputs from machine learning models built in collaboration between TTWF and MIT (using Python-based tools). Surface trends and generate flags for high-performing, at-risk, or stagnant learners and schools.
What you’ll bring
All qualificationsCore experience
- 1–2 years of relevant experience in analytics, preferably in education, nonprofit, or impact-driven sectors.
- Strong proficiency in Python for data extraction, modeling, and visualization (e.g., Pandas, Scikit-learn, Matplotlib).
- Experience with web scraping tools (e.g., BeautifulSoup, Selenium) and data integration from APIs or Google Sheets.
- Familiarity with data visualization platforms such as PowerBI, Tableau, or open-source dashboards (Streamlit/Dash).
- Understanding of machine learning model outputs, validation methods, and statistical testing.
Qualification wording
1–2 years of relevant experience in analytics, preferably in education, nonprofit, or impact-driven sectors.
Strong proficiency in Python for data extraction, modeling, and visualization (e.g., Pandas, Scikit-learn, Matplotlib).
Experience with web scraping tools (e.g., BeautifulSoup, Selenium) and data integration from APIs or Google Sheets.
Familiarity with data visualization platforms such as PowerBI, Tableau, or open-source dashboards (Streamlit/Dash).
Understanding of machine learning model outputs, validation methods, and statistical testing.
Education & alternatives
Requirements Required Qualification: Bachelor’s degree in Data Science, Statistics, Computer Science, Quantitative Economics, or a related field; Master’s degree preferred. Years of Employment Experience:
Posting record
Report an errorOpen 5 monthsWe first saw this posting 156 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 3, 2026156 days ago
- Recorded sightings
- 161
- Last seen by us
- Nov 6, 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
Teach the World Foundation is hiring
3 open jobs
- No new data jobs since June
See 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
- Power BI
- Tableau
- Matplotlib
- pandas
- scikit-learn
- Streamlit
Where the posting names them
4. Predictive Modeling & Advanced Analysis - Analyze outputs from machine learning models built in collaboration between TTWF and MIT (using Python-based tools). - Surface trends and generate flags for high-performing, at-risk, or stagnant learners and schools.
Technical Skills - Strong proficiency in Python for data extraction, modeling, and visualization (e.g., Pandas, Scikit-learn, Matplotlib). - Experience with web scraping tools (e.g., BeautifulSoup, Selenium) and data integration from APIs or Google Sheets.
- Experience with web scraping tools (e.g., BeautifulSoup, Selenium) and data integration from APIs or Google Sheets. - Familiarity with data visualization platforms such as PowerBI, Tableau, or open-source dashboards (Streamlit/Dash). - Understanding of machine learning model outputs, validation methods, and statistical testing.
Your next step
Complete your application on teachtheworldfoundation.zohorecruit.com. The employer’s form will show what is required.
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About the role
We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
Job description
Key Responsibilities
1. Dashboard Management
- Operate
and maintain the Learning Dashboard, which merges backend
data from TTWF and in-app platforms
- Support
the implementation of predictive models for student progress, attendance, and
learning risk levels.
- Generate
weekly insight reports for internal teams to identify schools or students
needing intervention.
2. App-Specific Analytics Monitoring
- Independently
access and interpret metrics from in-app dashboards to
assess real-time student engagement and learning trajectories.
- Reconcile
in-app data with internal assessment and attendance records to validate
learning trends.
3. School Health Index (SHI) Analytics
- Support
the generation and refinement of the School Health Index (SHI), a dynamic
bench-marking tool that compares school- and region-level performance.
- Help
ensure SHI accuracy through validation with field data and stakeholder input.
4. Predictive Modeling & Advanced Analysis
- Analyze
outputs from machine learning models built in collaboration between TTWF and
MIT (using Python-based tools).
- Surface
trends and generate flags for high-performing, at-risk, or stagnant learners
and schools.
- Identify
opportunities for content enhancement or field follow-up based on learning and
engagement patterns.
5. Data Pipeline Development & Automation
- Manage
and improve backend workflows including automated data scraping, cleaning, and
structuring.
- Support
or co-develop a centralized data warehouse to ensure seamless integration
across learning, operational, and assessment datasets.
6. Cross-Departmental Collaboration
- Work cross-functionally to integrate
findings into strategic decisions.
- Share
insights and recommendations in a clear, visual, and non-technical format for
diverse internal audiences.
7. Documentation & Reporting
- Document
analytical processes, data flow diagrams, and methodologies for continuity and
replication.
- Assist in
the preparation of visual dashboards and insight summaries for external
stakeholders and donors.
Requirements
Required
Qualification: Bachelor’s degree in Data Science,
Statistics, Computer Science, Quantitative Economics, or a related field;
Master’s degree preferred.
Years of Employment Experience:
- 1–2 years of relevant experience in analytics, preferably in
education, nonprofit, or impact-driven sectors.
Travel
or Location-Specific Requirements:
- Some travel to areas from head office
Preferred Experience, Background, or Skillset
Technical Skills
- Strong
proficiency in Python for data extraction, modeling, and visualization
(e.g., Pandas, Scikit-learn, Matplotlib).
- Experience
with web scraping tools (e.g., BeautifulSoup, Selenium) and data
integration from APIs or Google Sheets.
- Familiarity
with data visualization platforms such as PowerBI, Tableau, or open-source
dashboards (Streamlit/Dash).
- Understanding
of machine learning model outputs, validation methods, and statistical
testing.
Soft Skills
- Strong
analytical thinking and ability to translate data into practical insights.
- Excellent
organizational skills and attention to detail.
- Effective
communicator with the ability to simplify technical findings for
cross-functional teams.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Karachi, Pakistan
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.