Data Scientists are in demand. We talk about who they are and how to become one in the below podcast…
- Data scientist will usually have a masters degree or even a PhD and so a strong academic foundation is needed.
- Typically you will get an undergraduate degree in computer science, social science or one of the physical sciences with a grounding in statistics. Then there will be a Master’s degree or PhD in data science or a related field.
- You will also need to have gained proficiency in an analytics tool like R (https://www.r-project.org/) that is used to solve statistical problems and manipulate data.
- You would also be skilled in a programming language like Python, Java, Perl, or C/C++. About 40% of data scientists use Python as their main programming language.
- Other skills such as familiarity with Apache Hadoop (https://hadoop.apache.org/) , Hive (https://hive.apache.org/), Pig (https://pig.apache.org/), and Spark (https://spark.apache.org/) – all tools to process and analyze large data sets, and cloud tools like Amazon S3 (https://aws.amazon.com/s3/) is also an advantage.
- Understanding machine learning and how artificial neural networks, reinforcement learning, and other machine learning techniques work will be a huge advantage to you.
- Once you have data that means something you will need to present it in a way that other’s can comprehend and that’s where data visualisation comes into play. Visualising data with various visualisation tools like Tableau, D3.js, Matplottlib, and ggplot will be important skills to have as a data scientist.
- Naturally curious and a drive to want to find out “why” things are the way they are.
- Organized – You need to be able to organize data and results when handling lots of data points from many different sources.
- Critical thinker – It’s one thing to put data points on a chart it’s another thing to creatively and critically evaluate what it means and how it all fits together in the larger scheme of things.
- Focus – Working with data requires focused attention, often for long stretches of time, and an attention to detail without quickly getting board if the magical revelations don’t jump out at you immediately.
- Good communication – To get data, collaborate with others and communicate results to your employer, your communication skills need to be strong. To be able to communicate in a non-technical way to the company you are working for and give non-technical summaries and ideas of opportunities will be a key skill to have.