New masters dive into the world of big data

1 June 2017

Meet Eduardo Lynch, Pedro Fernandez and William De Azevedo: three recent graduates ready to springboard into the world of big data.

In May, UTS proudly celebrated the graduation of its very first Master of Data Science and Innovation (MDSI) cohort – an exciting and historic milestone for the university's ground-breaking two-year-old postgraduate degree. Eduardo Lynch, Pedro Fernandez and William de Azevedo made up the cohort which, though tiny in number, is oversized with enthusiasm to dive into the mystifying world of big data.

After accepting their testamurs in the UTS Great Hall, Lynch, Fernando and de Azevedo returned to their educational homeland at the UTS Connected Intelligence Centre and shared their thoughts on the MDSI program while celebrating with family, colleagues, peers and cake.

First MDSI Graduates

For Lynch, who came to the MDSI from a career in business management, the program opened up a number of exciting new professional pathways.

"It's changed me completely! The MDSI encourages you to really expand your skills and abilities. We gained a lot of knowledge, and most importantly we learned how to use that knowledge in industry roles."

The MDSI program is a unique program of study and the first transdisciplinary data science degree like it in Australia. The degree was launched to fill a global talent gap for data experts across a variety of industries, from oceanography and climate change mitigation to health policy work and market research. The goal is to produce graduates who have the technical ability to generate and interpret data combined with strong creative instincts and a clear understanding of business goals.

It also teaches adaptability and versatility, which Lynch is chuffed about.

"I took on the MDSI to change careers, and I know this degree is going to help me enormously as I go out there to find new work opportunities. I have the confidence now to approach large companies or pursue self-employment if that's the way I decide to go."

Lynch now works for an Australian business travel company, analysing data to drive efficiency and improve customer satisfaction.

Like Eduardo Lynch, Pedro Fernandez arrived at UTS looking to change his career trajectory. Before enrolling in the MDSI, he worked as a biochemist and ran his own business.

"I came to the MDSI wanting to switch gears in my life and start something new. I'd heard of data science at UTS and I got hooked on it through an information session where we took part in a brief collaborative data activity. I was accepted into the course and I can say now that it's surpassed all my expectations."

Fernandez has already been recruited as a data scientist by an Australian resources company and has set up his life in Orange, NSW.

The call for professionals who can make sense of data and help translate it into information that can feed innovation is increasing, and MDSI students develop skills at this intersection of creativity, innovation and data analysis. Crucially, they are also taught to develop a critical, human-centred perspective on big data and to think ethically and systemically about data and its applications.

Fellow MDSI graduate William De Azevedo is now employed at the NSW Government's Data Analytics Centre (DAC), and has also joined the MDSI teaching team as a casual academic. He's feeling more equipped to deal with the changing work landscape.

"Starting a new career is always challenging, but the MDSI has tested our abilities and prepared us to take on a variety of challenges. Students are free to choose the elective subjects that best fit with their professional objectives. This customisability makes the MDSI program really dynamic. Students develop multiple new skills to attend to the demands of industry.

"I also think one of the best qualities of UTS:CIC (UTS Connected Intelligence Centre) is the focus on the use of human-centred analytics in education. This guarantees the quality of the learning process of their students."

For all three graduates, participating in 'hackathons' was a highlight of the program. Hackathons are data science events where participants from universities and industry collaborate to develop algorithmic solutions to data challenges.

"Hackathons really helped me to get the experience I needed to start working as a data scientist," says de Azevedo.

"They're great events where you can use all the knowledge you've learnt and work collaboratively as a team," adds Fernandez. "You have to come up with ideas in a really short amount of time, so they are not only technically challenging but they're also very good at encouraging you to get creative, and to communicate your idea effectively because at the end of every hackathon, you have to pitch."

"I went to about seven hackathons last year. It's like an addiction – you're thrown into something you're not at ease with and you just have to get creative and deal with it. It's a great challenge."

The success of UTS's first three MDSI graduates is a testament to the degree's focus on industry preparedness and professional adaptability. In a few short years, the MDSI academic team has built a strong and vibrant network of industry partners, who collaborate with students on data challenges and present opportunities for future employment.

"I think that professionally, I came to the MDSI as an outsider and now I am finishing the course as part of a community – as someone who is included, someone with agency and someone who can be a game-changer," says Fernandez.

"I'm feeling much more empowered and there are lots of opportunities out there for employment."

Article adapted from original article written by Jack Schmidt at the Centre for Connected Intelligence with some awesome photos of the graduation celebrations of the three MDSI graduates!

Big congratulations to MDSI's first graduates and we warmly welcome you to the UTS alumni community!
Are you an alum who's still got some questions about the MDSI program? Current students Passiona Cottee and Yogitha Mariyappa are keen to share their insights on the course.

Q: Why do you all like the MDSI so much? 

Passiona Cottee: The strength of the MDSI degree is in its diversity! There's a free-range electives from any faculty (just so long as it builds towards YOUR ideal data science skillset). The varied teaching styles are great, so are the different formats and modes of interaction - from industry panels to student-led pre-hackathon tutorials.

And most of all, I like the the diversity of the students themselves. We all come from such different backgrounds, different domains, and it means we don't compete directly, and that creates is a real sense of fraternity. We're not just building a network. We're establishing an entire industry. The feeling of belonging this offers is a rare and unexpected benefit.

Yogitha Mariyappa: My experience as an MDSI student so far has changed my view of a big data professional - a data scientist to be more precise - completely. We not only learn how to implement algorithms on large datasets to get results, we also learn what to do with those results and how to be ethical in doing so.

What sets MDSI apart from other master's degree is the non-academic approach to learning. There is a practical component to ensure that students come out of their shell and develop crucial communication skills through CIC blogs, where students write about their learnings within their peer community. In my opinion, MDSI is a family!

Q: How has the MDSI prepared you for work?

Passiona: If you had told me when I started, that one year into this degree (remembering I'm only studying part-time), I would be offered a data science role then I would have found it hard to believe. I mean we all want a Masters degree to pay-off, but the pace of the degree and its results are unparalleled! UTS has a very strong reputation for being relevant to industry and this course exceeds it.

Yogitha:The Innovation Labs that are part of the MDSI program is a fantastic opportunity for students to work with live data to solve real world problems. Enabling students to choose from a list of industry projects in the tech space, these iLab projects are as close to getting real work experience as possible and are an important investment in one's career. MDSI students can explore and work with new tools and techniques in the area of their interest equipping them with the required exposure for future work to progress in their data science career path.

Q: Yes, but what actually IS Big Data? Break it down for me.

Passiona: Big data has all the hallmarks of a faddish buzzword (YES! Thank you!) but for now, it's not going away. So, I'll try and deal with it in an intelligible manner! It is generally accepted that the vast data collected and indexed by Google and Facebook is big data. But what about everything else? Large astronomical and astrophysical data sets have been around for decades. Sure, you had to book in time on large mainframes to run your calculations over days or even weeks, but it was big data. So what's changed? There are a few things going on.

First, it's a way of thinking. It's a willingness to replace assumptions with answers. It's about saying, 'let's not make assumptions, the answer is out there, let's go and find it!' Second, yes, it's the technology and hardware, the endless compute in the cloud that makes answering those questions possible. And, third, this one I've read about it and made sense to me, so I hope it helps with your understanding, too. Big data is about the granularity of data that is available about individuals. There is a now a level of detail about individuals that has never existed before.

Yogitha: Simply put, big data is "BIG" data. I know, stay with me here. Datasets in the Big Data domain are extremely huge to the extent of millions of rows and zettabytes, that may be structured in traditional databases or unstructured as seen in mobile phone interactions, email, video, audio, social media posts etcetera. This data must be analysed to find patterns and trends. Why? Because insights drawn from analysing such large data has the potential to solve business problems that to normal eyes seem unsolvable. My mantra since starting this course has been, 'All data has a story to tell. As a data scientist, you become a storyteller'.

Q: Why is data science and big data important, and why are data science professionals in such high demand these days?

Yogitha: With the massive explosion in data over the past few decades, it has become increasingly important to be able to mine data for valuable information. From online recommender systems in e-commerce to predicting diseases using Time-Series analysis in healthcare industry to even legally predicting the US election outcome, data science can be used to unlock the value hidden in big data and solve problems.

Passiona: Data science is the ultimate enabler for curiosity. I didn't want to be afraid of asking a question because I didn't know how to find the answer. The power of being able to enter any domain and start making discoveries is a highly compelling skill to have. When practised ethically, society has much to gain from practitioners of data science. Its potential to enhance the efficient allocation of finite resources to improve standards of living are immense.

Q: Can you tell us about the work you've found since starting the MDSI?

Passiona: Through participating in hackathons that were invitation-only (I only got in because I was an MDSI student!), I was able to make a good impression with the management of the newly-formed NSW Government's Data Analytics Centre. The centre is like a data science hub for the NSW Government and it encourages cross-agency data sharing. They offered me a temporary role and I took the plunge. I've gained incredible first-hand experience. It's so important to be applying what you're learning, as you're learning it and this role is allowing me to do just that as I continue to finish my degree.