6. Study pathways and careers¶
Verify everything on official websites before deciding. Programme names, entry requirements, fees, seats and scholarships change every year. The examples below were checked in October 2026 and are not endorsements.
What data work looks like after school¶
| Area | Typical work | Skills from this curriculum |
|---|---|---|
| Public health | surveillance dashboards, facility planning, programme evaluation | rates, mapping, bias audits, communication |
| Climate, environment, disaster risk | trend analysis, hazard maps, air quality, early warning | time series, uncertainty, geospatial |
| Agriculture | crop and price analysis, weather advisories, cooperatives | seasonality, regression, dashboards |
| Education | enrolment and learning analysis, school planning | tables, SQL, communication |
| Banking, finance, insurance | risk models, fraud detection, customer analysis | classification, evaluation, fairness |
| Government statistics and policy | surveys, census, budgets, monitoring and evaluation | sampling, cleaning, reproducibility, memos |
| Development organisations and NGOs | monitoring and evaluation, impact studies | experiments, causal thinking, reporting |
| Journalism | data stories, fact-checking | charts, rates, uncertainty, honesty |
| Technology companies | data engineering, analytics, machine learning, AI products | Python, SQL, Git, ML workflow |
| Research | academic and applied research in many fields | everything, plus mathematics |
Common job titles: data analyst, data scientist, statistician, M&E (monitoring and evaluation) officer, MIS officer, research assistant, GIS analyst, data engineer, machine-learning engineer, business-intelligence analyst.
Study pathways in Nepal (examples)¶
Computing and data * Computer Science / IT — e.g. BSc CSIT, BIT, BCA (Tribhuvan University and affiliated colleges); BE Computer or Software Engineering (Institute of Engineering, Kathmandu University, Pokhara and Purbanchal Universities). * Artificial intelligence and data science degrees — newer programmes are appearing: for example, Kathmandu University launched a B.Tech in Artificial Intelligence (2021) and has announced a Bachelor of Data Science; other universities list AI or data-science bachelor's degrees. Check current intakes. * Master's level — for example, Tribhuvan University's School of Mathematical Sciences offers a Master in Data Science (since 2021); MSc CSIT and other master's programmes in computing; statistics and mathematics master's degrees.
Statistics and mathematics — BSc/MSc Statistics, Mathematics, Applied Mathematics; actuarial science (often abroad).
Data-heavy fields with domain knowledge * Economics, Public Policy, Development Studies, Demography, Sociology. * Public Health (BPH, MPH), Nursing, Medicine — epidemiology and biostatistics. * Environmental Science, Geomatics Engineering, Geography, Remote Sensing/GIS, Agriculture and Forestry. * Engineering (civil, electrical, hydropower) — data from sensors and systems.
Diplomas and short courses — CTEVT and private institutes offer computer and IT diplomas; short professional courses (data analytics, GIS) — check quality and recognition.
Studying abroad¶
Many universities worldwide offer degrees in data science, statistics, computer science and AI. Compare: curriculum (maths and statistics depth, projects), language requirements (IELTS/TOEFL), total costs including living expenses, scholarships, work rights and recognition back home. Use only official university and embassy websites; be careful with agents who charge large fees or make promises. Scholarships to research include government scholarships offered through Nepal's Ministry of Education, Science and Technology, and those offered by foreign governments and universities (check each year's notices).
Skills employers ask for¶
Beyond tools (Python, SQL, Excel, a dashboard tool, Git), employers repeatedly mention: communication (explaining results to non-experts), problem framing (turning a vague request into a clear question), data cleaning and care with details, statistical judgement, ethics and confidentiality, and learning new tools quickly. Every one of these has been practised in this book.
Your one-page personal roadmap (activity)¶
Fill in and revisit every six months:
- My interests (fields I care about):
- Three skills I have (with evidence: a project, a certificate):
- Three skills I want next:
- Two programmes or courses to research — and the official page I checked:
- One project I will finish this year (question, data, deadline):
- One person I will ask for advice (a teacher, alumnus, professional):
- How I will keep my work honest and ethical:
Ethics you carry with you¶
Whatever path you take, carry the habits from this book: ask for consent, protect privacy, look for who is missing, report uncertainty honestly, credit sources, check your models for fairness, and never let a model alone decide what should happen to people. Data science is powerful because it affects real lives — in Nepal and everywhere.