Investigate data
Data Scientists clean datasets, inspect distributions, find patterns and decide which signals are worth modelling.
Role overview
What does a Data Scientist do?
Data Scientists explore data, test hypotheses, create features, train models and evaluate whether predictions are useful. The role connects technical analysis to practical decisions, so clear explanation matters as much as code.
Build models
They use supervised learning, classification, regression and evaluation metrics to compare model performance.
Explain outcomes
Strong recommendations explain what the model found, how reliable it is and what action a team should take.
Core skills
Core skills needed
The TechPathReady Data Scientist path focuses on six skill areas used in practical data science work.
Python
Use Python syntax, pandas, NumPy, notebooks and data cleaning workflows for repeatable analysis.
Statistics
Apply probability, hypothesis testing, distributions, sampling and confidence intervals to judge evidence.
SQL
Retrieve and combine data using SELECT queries, joins, aggregations, subqueries and filtering.
Machine Learning
Understand supervised learning, model evaluation, feature engineering, classification and regression.
Maths
Use linear algebra, calculus basics, vectors, matrices and optimization to understand model behaviour.
Communication
Explain insights, uncertainty, model tradeoffs and recommendations in language stakeholders can use.
Study sequence
Recommended learning order
Build a foundation in analysis first, then move into modelling and deeper mathematical understanding.
1
Python and SQL
Learn to clean, query and inspect data before attempting advanced modelling.
2
Statistics
Practise probability, sampling and hypothesis testing so your conclusions are defensible.
3
Machine Learning
Study classification, regression, features and evaluation metrics with small projects.
4
Maths and Communication
Use maths to understand algorithms and communication to turn model results into decisions.
Readiness scoring
How readiness is measured on TechPathReady
The Data Scientist readiness report combines role-weighted skill test results into a score out of 100. Each skill test has 5 topics and 20 total questions, so the Career Path Guide works as a focused Data Scientist readiness test.
Weighted skills
The report reflects the importance of each Data Scientist skill in the roadmap.
Topic coverage
Tests cover practical concepts across coding, statistics, SQL, modelling and communication.
Saved results
Completed full skill scores are saved in your browser and used in your readiness report.
Next steps
The report helps identify strong areas, weak skills and a focused study plan.
Next step
Check your Data Scientist readiness
Open the Career Path Guide, choose your country, select Data Scientist, and start testing the skills in your roadmap.
Open Career Path Guide