Gail Wittich

 

Gail Wittich. Data Scientist at Gaia Resources.

What is your academic background?

As a mature aged student, I completed Diploma of Business Programming Computer Power Training Institute, Certificate in 1995

  • Due to a change in jobs and moving cities, I stopped a Graduate Diploma in IT and Management, just 1 subject short of graduating!
  • In 2021, I completed the ‘Data Science Dream Job’ (DSDJ) program online.

 

Have you completed any other training in data science? 

 

If you pivoted into a data science role from another area, how did you go about this and what advice would you give others looking to do the same?

I have been around the IT industry for most of my career, earlier in Helpdesk and Desktop Support Management and later in Project Management.

There are lots of ways to become a Data Scientist, many of them free, if you want more support and structure I highly recommend the online, self-paced ‘Data Science Dream Job’ (DSDJ) program.

Go for it – Set your goals, start learning and code every day.

 

What sparked your interest in working with data?

Strangely enough, the posts on Facebook of crazy things like ‘Top 20 Countries by Population (1950 to 2100)’ caught my eye. See Animated Stats and others on YouTube. They are actually more like Business Analytics work, created with something like Tableau. But they reminded me that I like numbers and analysing reports etc. Machine Learning was very hot at the time. I looked at my options and discovered DSDJ, and it fitted my finances, timeline and requirements perfectly.

 

How did you come to work in your current role?

The DSDJ program is much more than Technical skills. One of the first modules is ‘Defining Success’. In short, define who, what, when, where do you want to be / do when you graduate. I had a ‘Success Contract’ written down and wrote it out twice a day, every day, throughout the program.

I am a Data Scientist earning $ _____ pa at an organisation in Perth, with a social conscience…I am free to travel and work from anywhere.

I applied for a role through an employment agency, Rayne Recruitment. The consultant, Erran Roser, was impressed by my resume, which included my personal Statement (another benefit of the DSDJ program):

Data Scientist with expertise in data preparation, visualisation and deep learning, employing Project Management, business and communication skills to improve business outcomes while respecting people and the environment.

Erran thought I would be a better match for another company. I met with Piers Higgs from Gaia Resources. The company and role he described were exactly what I had written in my Success Contract and Personal Statement. I have been at Gaia Resources for almost a year, and I am continually impressed by the values, ethics and professionalism of the whole team and the business. I couldn’t be happier.

 

What sort of projects have you been working on?

Gaia Resources is a Consultancy company working in the Environmental and Collections (think museums and archives) sectors.

  • I worked on a project to establish a new WA biodiversity data repository, as well as the national biodiversity data exchange project. They bring together disparate information on surveys of fauna and flora, and will underpin all environmental planning and approvals in WA and Australia.
  • I am involved in a project with the Queensland State Archive using text recognition of handwritten letters and documents from the 19th This will be an important component of ‘Truth Telling’ in Queensland and Australia. Look out for The Australian Wars on SBS in klate September 2022

They are exciting and significant projects that will improve the world we live in for everyone.

 

What tools/platforms do you use in your work?

Gaia Resources prefers to use Open Source software, over proprietary software, where ever possible. This protects our clients data and future proofs them, with the added bonuses of reduced cost to maintain and increased flexibility.

  • Python and its many wonderful libraries
    • TensorFlow
    • NumPy
    • SciPy
    • Pandas
    • Matplotlib
    • Keras
    • SciKit-Learn
    • PyTorch
    • Poetry
    • RDFlib
    • Difflib
  • GitLab
  • AWS
  • PyCharm
  • QGIS Geographic Information System
  • Google Workspace

 

What has been a highlight of your data science career so far?

Working with extremely talented and clever people – both clients and colleagues – who are also very generous with their skills and very unassuming. That’s refreshing and incredibly productive, resulting in extremely creative solutions.

 

What challenges have you faced as a data scientist?

It’s often tricky to know what area to focus on – you need to keep your skills up to date, but it’s not possible to be across everything.

 

In your experience, what are the best ways to communicate data science outputs to your wider organisation?

Visualisations are vital. That can be an image, a chart or an animated video. As long as it is based on the business goals and expressed in metrics that matter to the audience, you will be on the right track. A visual presentation to a team has been the way I have communicated most often. If the audience can then have access to the presentation afterwards, they absorb more information.

 

What’s the most surprising result you’ve found with data science through your work? 

I am really impressed with the success of Machine Learning Models in reading 19th Century handwritten letters and folios. Models have been well-trained and are very good – not perfect, but very impressive. Often the model is better at reading old handwriting than I am.

 

What would be your ideal job in 10 years?

I am not as young as many, (It’s never too late for a career change or pivot). I expect to be happily retired, enjoying the world we have impacted with improvements made possible by clever, principled Data Scientists.

 

What does the future of data science look like?

I am a terrible Futurist, even in my own industry and speciality.

I do think code-free Machine Learning will result in much more ML done by people in Admin rather than IT. That leaves Data Scientists free to do the more complex work.

 

For people considering a career in data science, what is one piece of advice you would give?

Go for it! Get involved in Hackathons, Meetups, start writing Python programs and do it daily (if you aren’t already a software engineer).