Data Scientist

What the job involves

A data scientist works with data at a deeper level than regular analytics. They collect and prepare data, test hypotheses, build statistical and machine learning models, evaluate their quality and explain the results to the team. Typical tasks include demand forecasting, fraud detection, customer recommendations and audience segmentation. The result only matters when it can be applied, so a clear link to the business problem is very important.

Skills you need

• Python and data libraries such as pandas and NumPy
• maths: statistics, probability, basics of linear algebra
• SQL and working with databases
• machine learning basics and model evaluation
• data visualization and clear explanation of findings
• Git and tidy documentation of research
• curiosity, discipline and a critical attitude to your own results

How to start and learn

Start with Python, SQL and basic statistics, then move on to classic machine learning methods and practise on open datasets. Build several projects with a clearly stated task, workflow and conclusions and publish them on GitHub. The course assumes a basic knowledge of programming and maths, so a beginner should first learn the fundamentals. Many people enter the profession through a data analyst position and then go deeper into modelling.

Where they work

In Armenia data science specialists work in banks and financial companies, startups and product companies, outsourcing studios and international teams, telecommunications and e-commerce, and as freelancers. There are fewer positions than for developers, and a solid foundation is usually expected.