Finding your first job out of University can be a daunting experience. It’s often difficult to know where to start or what skills and expertise employers are looking for. To help out budding young data scientists, the D2D CRC team members got together and brainstormed what they believe were some important steps that helped them get their foot in the door of the data science industry.

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“Learn and understand the central limit theorem” – Nick Lothian, Delivery Director

Data science is a strange mix of programming and statistics, and being a data scientist means knowing enough of each to firstly not be dangerous and secondly to create value. You’ll need more statistics than this during your career, but understanding this will help you avoid a lot of dangerous mistakes. See here.

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“Know your tools… and this means programming” – Grant Osborne, Data Scientist

You need to know your tools, and this means programming. Pick a programming language (probably Python) and become proficient in it. Learn how to use scikit learn, numpy and pandas. Working through code like Kaggle’s A Journey Through Titanic until you understand it and can write it yourself from scratch will also be very beneficial.

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“Seek internships and work experience” –  Jason Signolet, Machine Learning Specialist

Undertaking an internship or work experience with a company in the data science field not only lets you test the waters as to whether it is an area you may be interested in, it also allows you to gain invaluable business contacts as well as open up the doors for potential employment.

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“Do your research” – Andrew Feutrill, Project Lead

Data science is cross-disciplinary and covers a wide range of aspects including software engineering, mathematics, statistics, systems management and even business aspects. Taking the time to research different areas and how they apply to one another is not only beneficial and but will help you find a niche of your own.

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“Start a personal project” - Brodie Hamilton, Graduate Software Engineer

If you don’t have much experience working with data, starting a personal project is a great way to learn new skills. There are thousands of available API’s and open source software online that can be used. D2D CRC staff members have undertaken a variety of personal projects including designing data-driven applications and building interactive websites. This comes in handy if you ever find something online that you think could be done better – why not develop it yourself?

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“Take part in Kaggle competitions” – David Blockow, Software Architect

In addition to starting a personal project, Kaggle competitions are also a great opportunity to learn from others while also having a go yourself.  Kaggle is one of the few places online where you can find and use excellent datasets that are relatable to a commercial machine learning problem.

These are just some tips that the D2D CRC data science team found helpful to them. Hopefully some of the tips or ideas are useful for you too. Finally, good luck on your journey into data science.

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