Data Science is the Greatest Science! It is the Greatest Science for Women, as well

Data Science is the Greatest Science! It is the Greatest Science for Women, as well

Curator: Aviva Lev-Ari, PhD, RN


UPDATED ON 3/2/2018

The Growing Influence of Analytics on the C-Suite



This curation has three parts:

Part 1: Account of a Data Scientist, Aviva Lev-Ari, PhD – worked in Data Science, 1976-2005

Part 2: Meeting showcases women in data science – Stanford University, March 2018

Part 3: John Elder on Why Data Science Is the Greatest Science – Mega-PAW Vegas in June

Part 1: Account of a Data Scientist, Aviva Lev-Ari, PhD –

worked in Data Science, 1976 – 2005


Personal perspective on a professional life of a woman’s career is presented in

Reflections on a Four-phase Career: Aviva Lev-Ari, PhD, RN, March 2018



Corporate Applied Research in the US, 1985 – 2005 – Data Science at its BEST

Twenty years of top-tier management consulting and as a corporate executive. In the corporate world, I worked for Fortune 50, using the principles of Statistical Modeling, Economic Geography and of Industrial Organization Economics, every day.

LinkedIn Profile

1985-2005, worked at Director Level with Start-ups and Fortune 100 companies making presentations at the CEO Board Room level. Is reinventing work so that it works for the digital global economy. Consults and speaks to large and small groups. Lead webinars for universities, corporations and associations, and generally stir up conversation and inquiry on industry trends.
Startups: TimeØ Group, Concept Five Technologies, Inc., MDSS, Inc.; Top Tier Management Consulting: SRI International, Monitor Group; OEM: Amdahl Corporation; Top 6th System Integrator: Perot System Corporation; FFRDC: MITRE Corporation. In the Publishing industry: was Director of Research at McGraw-Hill/CTB. Researcher on Cardiovascular Pharmaco-therapy at Bouve College of Health Sciences, Northeastern University.

In 4/2012, have launched LPBI Group. She is an Executive-Entrepreneur with high energy and passion. Followed by 6200 Biotech professionals on LinkedIn and Group Manager of three Groups on LinkedIn.


Career in Health Care Followed Career in Analytics, 2005 – Present

Aviva Lev-Ari, PhD, RN

Director & Founder

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

LinkedIn Profile



Work experience in Health Care


  • Delivery of Care in MA – Post Acute Nursing Management positions, 2008 – 2012

HealthCare Delivery – Long Term Post Acute Care Nursing Management CV

  • Cardiovascular pharmacology-therapy research, development of a combination drug therapy, 2006-2007, Northeastern University, with Prof. Paul Aburjaily, PharmD


  •  Conceptual development with a Team of scientists on Drug Discovery & Drug Delivery, 2015-2016, LPBI Group, with Dr. Raphael Nir, SBH Sciences, CEO.



Amazon’s Aviva Lev-Ari Page

Discover books, read about the author, find related products, and more.



Part 2: Meeting showcases women in data science –

Stanford University, March 2018

Meeting showcases women in data science

In 2015, Margot Gerritsen, director of Stanford’s Institute for Computational and Mathematical Engineering, got tired of technical conferences that included no or few women speakers. “I always joke that this meeting was a revenge effect,” she said. “We wanted to showcase really amazing work that’s being done by women.”

Now, in its third year, the Women in Data Science conference included 17 women speakers and roughly 100,000 people listening on live stream or Facebook Live. More than 170 regional events in over 50 countries also featured their own panels of women speakers. Gerritsen, who is also a professor of energy resources engineering, said one reason for the meeting is to inspire women to enter and stay in the field of data science. “It’s still really tough for women not to feel a little isolated,” she said.

One outcome of the event has been lists of women worldwide who can speak about data science that are now regularly provided to meeting organizers looking for women speakers. “I would never have imagined that we would be reaching so many people,” Gerritsen said.

Women who attended the meeting reflected on their own experiences and the value of a community of inspiring women.

Lan Huong Nguyen

“As we have more women involved in data science and computer science and machine learning, companies can be shaped more by women. I think it’s always better to have a diverse perspective. Taking a different approach might lead to different conclusions or different innovations, both in terms of theory and in terms of products that are changing the way we live. More balanced input from both men and women would be beneficial for everyone.” —Lan Huong Nguyen, PhD candidate, computational and mathematical engineering

Margot Gerritsen

“I saw so many data science conferences where there were no female speakers or just one or two. I would ask the organizers why are there no women. One time they said, ‘Well, Margot, you couldn’t make it, so that’s why.’ At some point we said it is so hard to get existing conferences to change and we wanted to just totally cancel any argument that you cannot find excellent women. That first WiDS conference we live streamed because we thought it would be nice to try. It was such a success and we realized, ‘Oh my goodness, we are hitting something that people are so hungry for.’ But it is a bit pathetic we still have to do this in 2018. Honestly, there are so many fabulous women. At the start today I joked, ‘When you look at the program you see technical panels with really outstanding work by outstanding people and you may realize they are all women. We really tried to find some male data scientists but we just couldn’t find any.’” —Margot Gerritsen, PhD ’97, director of the Institute for Computational and Mathematical Engineering

Fatimah Al-Ismail

“Lately I’ve been trying to find inspirational women and looking for a role model, especially in STEM fields. It’s good to see that you have all these opportunities and there are people doing interesting things. People like you. It opens up a world of opportunities. In my country when I was growing up, women were expected to enter fields of either education or medicine, but I didn’t find myself in either field. I was on a scholarship from a company to study geophysics, but beyond the technical expertise the job required I didn’t know what other things I could do. I think this meeting shows you what options you have out there and how far you can go. It makes me believe in myself more and what I could do and the difference I can make in the world when I see all these women making a difference.” —Fatimah Al-Ismail, PhD candidate, geophysics

Emily Shah

“Data science occurred to me a year or so ago as a way to bring together the aspects I love about history with the skills I enjoy about math. Because the subjects I’m studying don’t lead directly into an application of data science, it was very cool this morning to see women applying data science in a range of ways and realizing how many options there are to be excited about. Over the next year, I will be writing a thesis on the way American media interpreted and potentially influenced the Tiananmen Square protests in 1989. I have been trying to figure out how to incorporate a data study or data visualization into that project. Being here today makes me much more comfortable about reaching out to people at Stanford and excited to talk and ask for advice.” —Emily Shaw, ’19, history and math

Risa Wechsler

“The very first time I was in a group of women like this was as a speaker at the conference for undergraduate women in physics. For me, that first time speaking to a group of women was totally mind-blowing. It’s just such an interesting energy. It feels so warm. I’m in a field that is about 15 percent women. In fields like mine and in certain areas of tech, some women do persist, but it’s not like it’s just the best women. It’s the women who are willing to put up with a certain level of isolation, and that means we are losing a lot of good people. I love my life and I love my job and I love my work, and it’s an incredible privilege to think about the biggest questions that we have. I just wish there were people from a broader set of groups who were able to ask those questions. Those are really universal questions that matter to everybody.” —Risa Wechsler, associate professor of physics and of particle physics and astrophysics

Daniela Witten

“When I was doing my PhD, the joke was that if you told people you were a statistician, then it would end the conversation. That’s no longer the case. Now people are interested in statistics and data science and machine learning. It’s really fun to be part of a field that people appreciate and see a need for. I don’t think a conference like this would have been possible 5 or 10 years ago. It’s really wonderful to see enthusiasm for data science, and especially enthusiasm among young women today for data science. It’s so important for these young budding data scientists to have the opportunity to interact with people who are more senior in the field and to have role models. We’ve heard talks about how it’s important to take risks in your career. I think there are a lot of risk takers in that room, and it’s pretty inspiring.” —Daniela Witten, BS ’05, MS ’06, PhD ’10, associate professor of statistics and biostatistics, University of Washington

Danielle Maddix

“My mom was a computational mathematician. It seemed normal to me growing up. Then as I grew older, I saw that it actually wasn’t that common. That’s why this meeting is so important for young girls to see these strong figures. Just to see so many strong women in the room together and know how that can encourage girls through the process is very important and powerful. I’ll be joining Amazon as a data science researcher, so it is encouraging to see people not only from academia but also in industry. It makes me feel more confident moving forward.” —Danielle Maddix, PhD candidate, computational and mathematical engineering

Bianca Yu

“When I first got interested in science, I really wasn’t aware that there was this disparity. I now realize that it’s such a big issue. It’s really important that there are events like this where you are inspiring other women to be interested in science and saying it’s OK. I have been working for the Institute for Computational and Mathematical Engineering and helping organize a list of potential speakers for this conference, and it’s been so exciting to read about all the women and their accomplishments. I’m interested in combining computer science with my bioengineering major, and I know those fields involve a lot of data science. That’s why I’m here. Seeing the speakers in person and seeing the passion they have about their fields and how far they’ve come is amazing. You can really feel the energy in the room.” —Bianca Yu, ’20, bioengineering

Alison Marsden

“I run the big math women’s group. As a grad student here I was a member of the mechanical engineering women’s group, and that was hugely important in my student experience. I tried to replicate that now that I’m a position to help. A lot of our women graduate students in math broadly speaking sometimes find themselves a little bit isolated, so we’re trying to build more of a sense of a community for them. They may be the only women in the research group or one of only a handful in their department or program. If we want to keep people in the pipeline, we don’t want them to be discouraged. I got really jazzed today when I got to sit in a room full of women in a technical meeting. Being here was a day of inspiration that I allowed myself in my really busy schedule.” —Alison Marsden, associate professor of pediatrics and of bioengineering

Elena Grewal

“One fact about Stanford Graduate School of Education is that it is extremely interdisciplinary, and there’s quite a lot of active research that’s quantitative in nature. So I took statistics and data science classes and economics along the way. It turns out that I had this very transferable skill set. I started out thinking it would be fun to do a summer internship at a tech company. Then I realized the work was amazing and I wanted to go for a full-time job. One of the really great things for women in industry is that there is a ton of momentum, especially around women in data science. Certainly there are fewer women in leadership positions. I’m very glad to be able to buck that trend, and hopefully that’s encouraging to others as well. Data science also has an advantage because it’s a new field, and people from different industries can enter. Some of those have more diversity, so it’s a natural advantage in creating a more diverse network.” —Elena Grewal, MA ’11, PhD ’12, head of data science, Airbnb

Judy Logan

“I am not technical myself. I’m a marketing person. But I’m a data-driven marketing person and I worked in tech for a lot of years, so I am always looking for ways to push the envelope for women. I like the fact that we’re able to bring this to the world beyond Stanford. With regional events, we’re able to highlight women from those regions, so women who might not have other speaking opportunities have a platform from which to share their research and to share their work. We actually were really trying hard to be in Saudi Arabia last year and we did not quite get there. And then this year we ended up having three regional events in Saudi Arabia. These are amazing women who are speaking. I think it’s wonderful that even in a place where women don’t really have a voice, they have a voice through WiDS.” —Judy Logan, co-director, Women in Data Science conference

Karen Matthys

“I recall many times I was the only woman engineer in a team and rarely ever saw a woman role model. I’d love to see more women in engineering pursuing advanced degrees and going to the next stages in their careers. We were brainstorming at the Institute for Computational and Mathematical Engineering several years ago on what to do, and we thought to have real impact we need to show those role models and inspire the next generation so that they can say, ‘Oh, I see myself in that person.’ That was really missing. We decided to pilot a Women in Data Science conference. We had 6,000 people pick it up on live stream the first year, so that’s when we thought, ‘Aha, we hit a chord here and we could have a much bigger impact if we try to reach out across the world.’ The question is then what do you do with all that bubbled-up energy and inspiration. That’s the most exciting thing – to see women take action and pursue their dreams.” —Karen Matthys, MBA ’88, co-director, Women in Data Science conference

Gerritsen is also associate professor of energy resources engineering and senior associate dean for educational initiatives in the School of Earth, Energy and Environmental Sciences, a senior fellow in the Precourt Institute for Energy, a member of Stanford Bio-X and of the Child Health Research Institute. Marsden is also a faculty affiliate of ICME, a member of Stanford Bio-X, the Cardiovascular Institute and the Child Health Research Institute.



Part 3: John Elder on Why Data Science Is the Greatest Science – Mega-PAW Vegas in June

Predictive Analytics World & Deep Learning World 2018

What exactly makes data science the greatest science?

We’re excited to announce that John Elder, Founder & Chair, Elder Research is confirmed to deliver a keynote address at the Predictive Analytics World Mega-Event, taking place in Las Vegas on June 3-7, 2018. This will be a joint, super-plenary keynote accessible to attendees of all five (5) Mega-PAW conferences: PAW Business, PAW Financial, PAW Healthcare, PAW Manufacturing, and Deep Learning World.

Description of Dr. Elder’s Keynote:

The Greatest Science

Data science, if judged as a separate science, exceeds its sisters in truth, breadth, and unity. DS finds truth better than any other science; the crisis in replicability of results in the sciences today is largely due to bad data analysis, performed by amateurs. As for breadth, a data scientist can contribute mightily to a new field with only minor cooperation from a domain expert, whereas the reverse is not so easy. And for utility, data science can fit empirical behavior to provide useful model where good theory doesn’t yet exist. That is, it can predict “what” is likely even when “why” is beyond reach.

But only if we do it right! The most vital data scientist skill is recognizing analytic hazards. With that, we become indispensable.

About John Elder:

John Elder, Ph.D., chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, and Washington D.C. Dr. Elder co-authored 3 award winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia, and was named by President Bush to serve 5 years on a panel to guide technology for national security. 

Dr. Elder’s keynote is not the only proof of PAW’s continued commitment to hosting the brightest, sharpest minds in data science and machine learning. When you attend PAW in Las Vegas this June you will witness only the the most inspirational keynotes and actionable workshops including:

… and many more. 

Predictive Analytics World is the place to meet peers, new partners, and get up to speed on the industry’s latest developments and opportunities. The networking is like no other. Don’t miss the biggest PAW event to date.



From: Gregory Piatetsky <editor1=kdnuggets.com@mail139.sea22.mcdlv.net> on behalf of Gregory Piatetsky <editor1@kdnuggets.com>

Reply-To: Gregory Piatetsky <editor1@kdnuggets.com>

Date: Monday, March 12, 2018 at 11:25 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: John Elder on Why Data Science Is the Greatest Science – Mega-PAW Vegas in June

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