As a psychology student at Victoria University of Wellington, Emma Vitz took up courses in statistics. She found out she was more interested in the latter, and graduated with a double degree in psychology and statistics.
“I liked that you could take all of this data and find insights from a whole bunch of data points,” says Vitz, who also worked as an intern at TradeMe.
Today, Vitz is an actuarial analyst at Finity Consulting in Auckland, working on “really cool data trying to help people understand risk better”.
She has been involved in several projects involving geospatial analysis such as predicting flood in New Zealand, and seeks to continue developing her geospatial skills and applying them to natural perils, climate change analysis and other geospatial projects.
“Pretty much every field needs to understand the data,” she says, and this is a message she wants to share as one of the speakers at this year’s Women in Data Science (WiDS) conference to be held tomorrow in Wellington.
“Data science provides an endless career pathway,” says Kate Kolich, director of data systems and analytics at the Social Investment Agency, and one of the New Zealand co-ambassadors (the other is Dr Mary Ellen Gordon, masters in information management programme director at Victoria University of Wellington) for the annual WiDS conference.
Like Vitz, Kolich started in an adjacent field, information technology.
Prior to joining SIA, she had worked as a programmer at the Ministry of Agriculture and Forestry (Now Ministry for Primary Industries) and later on at Bank of New Zealand where she held a number of business intelligence and analytics roles.
She has been active in promoting STEM and data science across the wider community, and today is the New Zealand co-ambassador for the Women in Data Science (WiDS) Wellington.
Every year, on the week celebrating Women’s Month, a series of events are held across the globe, featuring female data scientists in industry and academia talk about their work.
WiDS Wellington is an independent event hosted by Victoria University of Wellington to coincide with the annual Women in Data Science conference held at Stanford University and over 100 locations worldwide.
WiDS Wellington is a one-day technical conference that provides an opportunity to hear about the latest data science-related research in a number of domains, learn how leading-edge companies are using data science for success, and connect with potential mentors and collaborators in the field, explains Kolich.
This is Kolich’s second year as NZ WiDS ambassador.
“I have continued as a WiDS ambassador this year as it is a great opportunity to showcase the diversity of career pathways available in data science and data management,” says Kolich.
“I am passionate about encouraging the future pipeline of females and all young New Zealanders to see what a career in data science has to offer,” she adds.
“WiDS Wellington is also great way to provide female role models for the future generations of data professionals.
Kolich notes how the WiDS Wellington conference coincides with the first week of Victoria University’s new Data Science degree.
She says while the speakers at the conference are all women, it is open to everyone.
“We want to showcase what is possible with data and the types of roles that people can go into as data professionals,” she says.
The conference, while open to all genders, specifically have women speakers.
She says the conference was organised to make the discussions accessible to all genders and skills.
The learner track is intended to get people interested in what data science is all about. The professional track will highlight some of the cutting edge work being done by female data scientists, she explains.
Agate Ponder-Sutton, data scientist at BNZ, for instance, will talk about what a data scientist does, while a panel discussion of how it is like to work in the field will be moderated by Emma Vitz.
Gordon says the underrepresentation of women in the data science field is the reason why Stanford University started its annual data science conferences.
“Data can be used to better understand whatever problems you have,” she says, on the importance of the role data professionals in an organisation, both in government and in the private sector.
“When you do not have data, you are just talking about my opinion versus your opinion. But if we have got this data, we are able to look more deeply at what is going on.”
Dr Donna Cormack will talk about what data scientists need to know when working with Maori data, while Dr Sally Akevai Nicholson will talk about NLP for indigenous languages and Vidette McGregor from NIWA will deliver a talk on ecosystem modelling.
Amanda Hughes of Nicholson Consulting will discuss ethics for algorithms.
Kolich says support from host VUW and government agenciesStats NZ, MBIE and SIA as well as the industry - Enterprise IT, BNZ, Revera, Redhat and Finity consulting - allowed them to hold the event for free.
The event can also be viewed via livestreaming.
She says the attendees can choose from a range of tracks, such as “Data Science in New Zealand Organisations” which will include talks from Kari Jones(Air New Zealand) and Dr Kathryn Hempstalk (Trademe).
This will be an opportunity to hear about technical advancements in two of New Zealand's leading organisations and the track will also include a presentation from Kat Greenbrook (Rogue Penguin) who will deliver a talk about data visualisation and communication.
The “working in data science” track will include a panel discussion facilitated Emma Vitz(who also spoke at the 2018 WiDS event in Auckland) and established data scientists including Ernestynne Walsh (Nicholson Consulting), Fiona Thomson (Social Investment Agency) and Dr Lisa Chen (Harmonic Analytics).
There will also be an opportunity to try out some data science tools with the lab sessions.
The event highlights the increasingly important role that women are playing in data science, helping to break the glass ceiling and inspiring more women into STEM to make an ongoing difference, says Nasca Peng, a statistical analyst at Stats NZ.
Peng is also one of the speakers at the Wellington conference, on the topic of ‘Open Data Reimagined: Protecting Privacy While Sparking Insights’.
Peng says the programme further enhances the interaction between government, industry and academia in the field of data science.
The discussions are a culmination of intellectual brainstorming and practical exploration of data, and will encourage collaboration in this area across disciplines and sectors, says Peng, who has a degree in mathematics and a masters in data science - health informatics.
Spotlight on data scientists
Recent research reports from Gartner highlight the importance of having diverse data science teams, as espoused by many of the speakers at WiDS.
Consider that the diversity of data science applications and aspects requires a diverse team, including but also moving well beyond, gender and ethnic diversity, says a report by Gartner analysts Alexander Linden, Carlie Idoine, Peter Krensky and Neil Chandler.
“World-class data science not only needs introverted, extroverted, funny and dead-serious team members, but also members from diverse cultural, ethical and academics backgrounds, to cope better with the range of aspects" of their work.
So where can they find these team members?
Organisations can consider diverse recruitment channels, including employee referrals, online job boards, and unconventional approaches such as social networking sites, they state.
For more junior positions, potential candidates can be identified through linkages with schools and universities with graduate programs or with independent bodies. Many data science professionals also attend conferences, or join meetups.
Universities are coming to the rescue in bridging this talent gap.
One of the report authors, Peter Krensky notes that there has been a record number of undergraduate and graduate degrees in the field in recent years.
At the same time, he says recent report noted how fewer than a third of the top 100 global universities offer degrees in data science.
Public universities are rapidly building programmes to meet this student demand, he states.
Another Gartner research looks at steps organisations can take to retain this critical talent.
Many organisations are launching data science teams without a clear understanding of the breadth or depth of needed skills, both technical and non-technical, according to the Gartner report Taking care of data scientists
The result is a mismatch of expectations and capabilities that impedes progress toward transformative business outcomes, according to the report authors Alexander Linden, Carlie Idoine, Jim Hare and Erick Brethenoux.
They note how data scientists, especially new PhD graduates in machine learning (ML), often lack experience and expertise in specific industry and application domains, as well as in business understanding of the organisation’s mission-critical objectives.
Meanwhile, IT and business leaders often expect the data scientists to be equally expert in data and analytics infrastructure, enterprise architecture and ML operations, all of which are needed to support data science projects.
“The critical tasks needed to build a sustainable data science capability require more than a flair for writing algorithms,” they point out.
They need an array of quantitative, IT, business and people skills, manifested in a mix of data science and other supporting roles. The right mix and balance of both skills and roles are essential to accomplishing the data science tasks that lead to business impacts.
The Gartner analysts say it is also important to expand the data science team’s capabilities with software and hardware specialists in support roles such as data engineers, business analysts, enterprise architects and DevOps.
“Data scientists don’t, or at least shouldn’t, work alone in a vacuum,” they state.
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