What is a Data Scientist? – Definition of a Data scientist

Definition of a Data scientist – Wyatt partners Data analytics Perspectives

Wikipedia says – Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge

It would follow that a data scientist is someone who does that shouldn’t it? Well as with so many things in adult life and ironically totally at odds with the logical backgrounds of most data scientists, the answer is Yes & No

Yes, they should be able to do various aspects of that but Not necessarily all of it.

From a practical point of view for hiring managers or people wanting to enter the sector what skills do you need to be a data scientist?

A numerate or quantitative degree ideally also something that develops scientific or critical reasoning.

Exposure to data science techniques like machine learning, algorithm libraries and coding particularly in open source tools

Python, SQL, Matlab & R – It’s important to note that Matlab rarely features in commercial organisations.

Learning to clean and manage unstructured data is the most critical skill of a data scientist and exposure to this should be the focus of entrants to the market place.

To sum up the essence of a Data scientist

We are looking for,

  • Critical reasoning
  • curiosity is an essential trait
  • interdisciplinary skills across Science, behavioural anaylsis, analytics, & Business

You will need specific experience in tools, concepts & mathematical models detailed below

Open Source Coding and experience of Statistical models now very much part of the data science toolbox, like Machine learning types of models we might expect a data scientist to be familiar with.

  • Regression
  • Classification
  • Clustering
  • Dimensionality Reduction.
  • Ensemble Methods.
  • Neural Nets and Deep Learning.
  • Transfer Learning.
  • Reinforcement Learning.

It is important to remember the Interdisciplinary element of Data science, Not all of the skills will be needed all of the time.

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