WiMLDS NYC “Careers in AI” 2021 Virtual Kickoff Event with Dataminr
A two-hour event hosted by the NYC Chapter of WiMLDS in partnership with Dataminr, one of the world’s leading AI businesses, was held on June 10, 2021. It featured eight accomplished panelists, with varied career paths in both industry and government, and gave chapter members the opportunity to learn about career options related to artificial intelligence, machine learning and data science. All participants were able to expand their professional networks by connecting directly with the panelists in smaller breakout rooms and with each other through a series of one-on-ones.
The event began with an introduction by NYC Chapter co-organizer Melissa Barr, a Dataminr overview by Sarah Manning, and panelist introductions by co-organizer Ellie Norris.
Panelists:
- Nour Fahmy: Data Scientist, #paid
- Rui Bai: Data Scientist, Dataminr
- Shengli Hu: Research Scientist, Dataminr
- Serena McDonnell: Senior Data Scientist, Delphia
- Somaieh Nikpoor: AI/ML Research Advisor, Government of Canada- Research & Innovation Unit
- Alison Renner: Sr. Research Scientist, Dataminr
- Isabel Zhang: Sr. Research Scientist, Dataminr
- Sarah Manning: Director of Engineering, Dataminr
Panel Questions & Featured Responses:
#1: “What is your current job role and could you describe the path you took to a career in AI?”
Shengli Hu:
“I’m a Research Scientist at Dataminr. I’ve been mostly focusing on Computer Vision projects ever since I joined the company two years ago. I was originally trained as an operations researcher and as a behavioral economist/experimental economist. When I was a grad student, those fields were experiencing an influx of AI and machine learning and that’s how I got to take all the graduate courses in the Computer Science department at Cornell University. At one point, I decided this field was much more exciting than my original field, and so I decided to publish in this field instead, and that’s what led me to where I am right now.”
Alison Renner:
“I am a Research Scientist at Dataminr. I’ve been at Dataminr for about 3 months and I come from a background of human AI interaction. I took an interesting path to AI; my undergrad was in Math with a minor in Computer Science and I started as a Software Developer when I graduated in a team of engineers who were building AI tools, but without thinking about end users, and I put myself in the role of the user-focused side. Then, I went back to get my PhD with a focus on HCI and AI to get a formal education and real world applications.”
Isabel Zhang:
“I am a Research Scientist from the AI team at Dataminr. I’ve been with Dataminr for 2.5 years. I come from a background of Human Systems Engineering; the goal of this is when we design systems, we need to have humans on our mind. I’ve always been interested in how to make technology better and easier for humans to use and I got started in that by working with Data Scientists and Research Scientists on Natural Language Processing (NLP) and Computer Vision (CV).”
Sarah Manning:
“I am a Director of Engineering at Dataminr. I manage the core Data and Analytics team. I trained in Math, specifically Differential Geometry, as well as Painting and Fine Arts. Data was always a passion of mine, so I moved into the data realm, taught math for a while, got experience with the product side and education. I had my own company for a while, and I decided I wanted to work with big data so I worked for an e-commerce company, Etsy, and then joined Dataminr because I was interested in working with streaming data.”
#2: “What are career tips that you would provide to women entering the field of AI or data science?
Nour Fahmy:
“Your success in your role is dependent on the resources your employer is willing to allocate to your projects. Make sure you do your research to ensure your position is well supported.”
“As qualified as you may be, your opportunities are as good as your network. Make sure to reach out to people whose work you look up to. Don’t underestimate how important it is to have someone you look up to vouch for you.”
Rui Bai:
“Data science is a combination of domain knowledge, math and computers. The importance of domain knowledge in data science actually indicates a huge opportunity for everyone. So, for example, if you really love music, Spotify has a lot of great data scientists working on music patterns. Find the field that interests you the most and then you can always find a job in that area to use your talents and skills in data science.”
Serena McDonnell:
“When looking for a job, consider the 3 Cs: Credentials, Contacts, and Credibility. Credentials can come from your education, Contacts come from the network you build, and Credibility comes from your portfolio.”
“If someone puts you down, it’s a reflection of them, not a reflection of you.”
Somaieh Nikpoor: “My advice is for those who want to become a self-taught data scientist:
(1) Do more hands-on projects. It is often hard to properly understand some of the theoretical concepts. Hands-on learning helps you to not only understand theory better, but to obtain work experience.
(2) Network more. It will help you develop and improve your skill set, stay on top of the latest trends in your industry and it opens the door for newer opportunities.”
We are extending a big thank you to our panelists and attendees!
You may connect with us through:
- ☎️ Meetup
- 📩 nyc@wimlds.org
Additional Information:
Dataminr is one of New York’s top private technology companies fueled by employees who have a passion to collaborate and make a difference. Check out career opportunities with Dataminr.
NYC Chapter Co-Organizers: Melissa Barr & Ellie D. Norris
