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WiDS (Women in Data Science) New York @IBM - February 26 2021

By Vanishri Murali posted Fri February 12, 2021 11:09 PM

  

WiDS New York @ IBM is an independent event that is organized by NYC WiDS Ambassadors associated to NYC as part of the WiDS Worldwide Regional events organized by Stanford University and an estimated 150+ locations worldwide, which features outstanding women doing outstanding work in the field of data science.


Click here for replay of the event You will find it under the Videos tab. There are more videos of such events in future.

(Please join us in this virtual event on the Friday, 26th of February 2021 from 11:00 am EST to 3:00 pm EST
Click here to register: WiDS New York @ IBM)

Agenda:wids-2color-1line.png

Introductions and Welcome

by Vanishri Murali   WIDS Ambassadors

The growing role of Prescriptive Analytics in Business
by Serena Bellesi , Ph.D.Chief Data Scientist, Machine Learning and AI Program Director IBM Global Markets

 Merging internal and external provided solutions for to meet analytics and reporting needs
As part of Colleen’s role in developing and implementing the Investment Manager Services division’s data analytics program, the team has had to adopt both external vendor solutions and integrate these with customized in-house solutions which is a common theme for many firms. Colleen will walk through why they decided to buy vs. build across various points in the Analytics process including data warehousing, report generation and client access.
by Colleen Ruane Director of Data Analytics SEI

Data-Driven Job Capability Profiling
Automated identification of soft skills requirements in the marketplace has been sparse at best despite the recognition of the importance of soft-skills in a successful career. We propose a data-driven approach based on deep learning to identify the soft skills requirements from job descriptions with almost 80% accuracy. We show that the capabilities requirements change as employees transition from one position to the next, and also as organizations transform from one focus area to another.
by Bhavna Agrawal Research staff member at IBM T.J. Watson Research Center in Yorktown Heights, NY
JobCapabilityProfile_NYWids2021.pdf


Q&A

Data Science as a Team Sport
Data Science careers are in high demand, with many job opportunities and attractive salaries. As a relatively new career, it is ambiguously defined, and the job description of a data scientist can vary greatly from company to company. For those reasons, Data Science has attracted both new grads and career changers from all sorts of different fields. For Statisticians, Data Science is an exciting opportunity to apply your hard-earned skills to a variety of interesting and challenging problems. Having a solid Statistics background will give you a head start in that direction. However, Data Science is much more than pure Statistics knowledge. Being able to recognize and take advantage of a team with a diverse set of experiences will provide you with a unique opportunity to grow individually while benefiting your entire team. In this talk, I will walk you through my career journey, the different roles a Data Scientist can take, useful skills for a successful career and lessons learned. 
by Gabriela de Queiroz Sr. Engineering & Data Science Manager at IBM 
DS_as_TeamSport_2021-02-26_WiDS_NY.pdf

Data Science and Mental Health
The application of data science in the mental health industry can be used to improve how mental health disorders are diagnosed and treated using data analysis, machine learning, and AI.
by Caroline Cameron Data Analyst at IBM GTS, Delivery & Integrated Operations
Datascience_MentalHealth_WiDS_NY_2021.pptx


Why data science projects fail to scale?
Research suggests that more than 85% of data science & AI projects never see light at the end of the tunnel. This session is aimed to share 10 pitfalls to avoid as you embark on your data science journey.
By Sheetal Rishi Director, Cloud & AI executive in IBM’s Global Markets

Q&A

Sentiment analysis of Twitter feed for hashtags related to remote working
There is no doubt that one of the major changes due to COVID-19 is forcing many people to work from home. That action changed the lives of millions of people across the globe, in addition to the way of running many businesses nationally and globally. The people’s experience and opinion about the remote work setting might give managers ideas about the pros and cons of making work remote. The analysis is built based on 50,000 tweets collected from Twitter, as Twitter is one of the popular social networking platforms. The tweets were collected from five different hashtags: #remoteworking #remotework #workfromhome #workingfromhome and #futureofwork. Sentiment analysis, topic modeling, and network visualization were done to analyze the opinion of the crowd on Twitter. The presentation includes the results found based on the study.

by Roshani Bharati  Ph.D. student in Business Data Science program at Martin Tuchman School of Management, NJIT & Nesreen El-Rayes  Lecturer II at Kean University(School of Management and Marketing - Business Analytics Concentration) and part-time Ph.D. student in the second year in Business Data Science Program at Martin Tuchman School of Management, NJIT

Own the Growth: Trends and Opportunities in Data Science and AI Adoption
Given Jessica’s unique position within the Data Science and AI space, she will walk through what she is seeing across industries and within verticals. This is a great opportunity to get a better understanding of wherevarious industries stand with Data Science and AI adoption, and also potentially get a few ideas that you can bring back to your own sector.
By Jessica Kowalski Head of Data, AI, ML - Accenture AWS Business Group, Amazon Leader | Data, Analytics, AI & ML Growth | Board Member

Q&A

Path forward and Career Discussion with Speakers and Ambassadors
Networking and Interactive session Open for all

More about Our Speakers

 
Serena Bellesi
Serena Bellesi is Chief Data Scientist and Machine Learning and AI Program Director at IBM Global Markets

Serena has helped many clients and IBMers to achieve outstanding business results, with the use of Data Science, Machine Learning, and AI.
She has guided the first team of Data Science Apprentices at IBM, who joined the program with no previous coding, educational, nor professional background in analytics, and are now advanced Machine Learning engineers.
Serena is advising professors and instructors in the NYC area on ways to incorporate Data Science in their curricula, and she is mentoring college students and coworkers who are interested in starting a career as Data Scientists.
Serena is a recognized Data Science Thought Leader at IBM and with the Open Group, a Certified Project Manager (PMI), and Blue Core Coach

Serena holds a Ph.D. in Economics, Mathematics and Statistics from Sapienza University of Rome and has been a Visiting Scholar at Columbia Business School.

In the past, she worked as a Lecturer in Macroeconomics and Finance at Sapienza University of Rome, and as a fundraiser and project manager for several SMEs, NGOs, Universities.
Before joining IBM, Serena worked as a Data Science consultant and helped many financial clients to embrace the ML journey.

Serena is an Ambassador at Women in Data Science at Stanford and a recognized speaker at several conferences in Machine Learning and AI. She is also a Subject Matter Expert on Decision Optimization, Digital Transformation, Natural Language Understanding, Time Series models, and on Machine Learning and AI applied to Economics and Finance, Media and Advertising.




Colleen Ruane

Director of Data Analytics SEI

Colleen Ruane is responsible for developing and implementing the Investment Manager Services division’s data analytics program. Colleen leads the data analytics team, which explores ways of integrating analytics, machine learning and artificial intelligence (AI) into our platform. She also works with non-technical/non-analytical consumers of data and helps them understand how to put analytics into practice.
Her areas of expertise are:
Exploring new technologies in data management, visualization and machine learning
Helping non-technical/non-analytical consumers of data put analytics into practice
Using data and analytics to construct narratives and tell stories

Colleen has 15 years of experience with data analysis, risk analytics and system engineering. Prior to her role as Director of Data Analytics, Colleen worked for 10 years at ITG with roles in product management, analytical research and relationship management. She also worked for Lockheed Martin with their System Engineering team writing algorithms for large-scale scheduling and planning systems.

Colleen has a Bachelor of Science degree in Math from Loyola College, and a Master of Science degree in Systems Engineering from the University of Pennsylvania.



Bhavna Agrawal

Bhavna Agrawal is a research staff member at IBM T.J. Watson Research Center in Yorktown Heights, NY, working on developing AI application for industrial use cases. She has been with IBM for over 20 years since receiving her PhD in Electrical Engineering from Rensselaer Polytechnic Institute, Troy, NY (USA).

She started her career in VLSI Design Automation, developing circuit simulation, timing and tuning tools. This was followed by small duration in services delivery automation, where she developed compliance process automation tools and techniques.

Bhavna has been working in the field of AI application for the last 5 years. Specifically, her currents interests are in Natural Language Processing (NLP) related AI applications development, in industries like education, hospitality, and industrial manufacturing.




Gabriela de Queiroz
Gabriela de Queiroz is a Sr. Engineering & Data Science Manager at IBM where she manages and leads a team of developers working on Data & AI Open Source projects. She works to democratize AI by building tools and launching new open source projects.

She is passionate about making data science available to everybody and is actively involved with several organizations to foster an inclusive community. She is the founder of AI Inclusive, a global organization that is helping increase the representation and participation of gender minorities in Artificial Intelligence.

Gabriela is also the founder of R-Ladies, a worldwide organization for promoting diversity in the R community with more than 180 chapters in 45+ countries. She has worked in several startups and where she built teams, developed statistical models, and employed a variety of techniques to derive insights and drive data-centric decisions.



Caroline Cameron
Caroline Cameron is a Data Analyst at IBM GTS, Delivery & Integrated Operations. She initially joined the company as a Data Analyst Apprentice and currently develops internal applications.

Caroline is also passionate about AI and blockchain.

Caroline graduated first in her class, Summa Cum Laude, with a B.S. in Psychology from Campbell University. She transitioned into data science and joined IBM after previously working as a paralegal for several law firms.




Sheetal Rishi
Sheetal Rishi is the Director, Cloud & AI executive in IBM’s Global Markets. She is responsible for driving innovation using AI, Machine Learning, technologies in hybrid multi-cloud environments.
At IBM she has held various roles including strategic partnerships building for Watson and Cloud platform with Global System Integrators and Independent Software Vendors, head of Banking Product Management and AI consulting partner.
Before IBM, Sheetal has led several strategic consulting engagements in Asia, Europe and North America working at McKinsey & Company and  Citibank's North America Corporate Re-engineering team.
She is passionate about fostering relationships between man and machine for the broader goodness of humanity.
She lives in New York with her husband and 3 kids. She is an active volunteer in her community for activities related to education, social goodness and the advancement of a diverse workforce in the tech sector.



Roshani Bharati
 Roshani Bharati is a second year Ph.D. student in Business Data Science program at Martin Tuchman School of Management, NJIT. She received her undergraduate degree in Industrial Engineering from Tribhuvan University in Nepal, Master’s degree in Business Administration from Asian Institute of Technology in Thailand, and a M.S. degree in Management Information System from University of Nevada in Las Vegas, Nevada. She is currently exploring the use of data science techniques to enhance reader’s experience/engagement in digital platforms. Ms. Bharati has a combined 3 years of work experience as a Supply Chain Manager in power industry and as a Service Engineer in automobile industry of Nepal. She is also the recipient of prestigious Doctoral Provost Assistantship at NJIT, among several other academic awards/scholarships received in her academic career.



Nesreen El-Rayes
Nesreen D. El-Rayes is a part-time Ph.D. student in the second year in Business Data Science Program at Martin Tuchman School of Management, NJIT. She is also a full time Lecturer and academic adviser at Kean University in the School of Management and Marketing (Business Analytics Concentration). She received her MS in Business Analytics from the University of Michigan-Dearborn, her MS in Management of Technology from Nile University, and her BS in Information Systems from Cairo University. Her research interests include data mining, visualization, and supply chain analytics. Nesreen has experience in areas spanning Process and Performance Management, Decision Support, TQM, Business Analytics, Innovation Support, Training and Teaching.




Jessica Kowalski

Jessica Kowalski is Head of Horizontal Solutions - Accenture AWS Business Group at Amazon Web Services (AWS)

Jessica is a disruptive data, analytics and AI business leader with 18 years of experience in the public and private sectors. From early work delivering profiling systems for US Intelligence organizations like the FBI and DHS to her more recent focus on building analytic product portfolios for content providers like Lexis Nexis, Elsevier and AWS, Jessica’s career spans 360 degrees of data-driven business.  She’s passionate about the translation of complex solutions to non-technical audiences to inspire innovation and produce remarkable outcomes.
Jessica is a self-professed data science geek, storyteller at heart and steadfastly devoted to sustaining and advancing diversity in leadership at all levels of business. She currently leads Amazon’s global Data, AI, ML business with Accenture, a multi-billion dollar channel. Her industry experience spans Government Intelligence, Defense, Banking, Capital Markets, Consulting, Insurance, Pharma, Biotech, STM and Higher Education. She lives in NY with her husband and two daughters and is an active founding member of the Women’s leadership group, Chief



Our Ambassadors:

Apoorva Nitsure
Erin Stanton
Nosaiba Dar Mousa
Rellie Luo
Taida Buljina-Prohic
Tharangini Palanivel
Vanishri Murali


Check the 2020 WiDS video

Feel free to check out the WIDS Worldwide conference
Also check out the WiDS UAE


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