Elevating the Experiences of Women in Data

New York | May 21, 2020

Sponsored by

DATA SCIENCE SALON ELEVATE IS A UNIQUE FEMALE FOCUSED CONFERENCE WHICH BRINGS TOGETHER SPECIALISTS FACE-TO-FACE TO EDUCATE EACH OTHER, ILLUMINATE BEST PRACTICES AND INNOVATE NEW SOLUTIONS IN A CASUAL ATMOSPHERE WITH FOOD, GREAT COFFEE AND ENTERTAINMENT.

Register now

Early Bird Ticket

Individual

$99

All sessions | Regular seating
Food included | Opening reception

About

Get access to powerful decisionmakers in data science in an intimate setting at Data Science Salon Elevate, the leading female-focused industry conference series around applications AI and Machine Learning. Learn from practitioners, technical experts and executives how to solve real-world problems by harnessing disruptions in data, artificial intelligence, machine learning, and cutting-edge technologies. Workshop real-world issues with other attendees, like overcoming imposter syndrome, connecting with mentors, and navigating non-traditional career paths. At DSS Elevate, we connect you with our powerful community face-to-face and digitally – each ticket comes with one year of access to DSS Insider, the content repository for all Data Science Salons.

Data Science Salons are one- or two- day events hosted at Blue Chip companies. Over 50% of our 200-500 attendees at each conference are data decisionmakers (Sr. Data Scientists and above). And we are the only data science conference with a gender balance in our speaking roster, even beyond our female-focused events.

sample of topics covered:

Machine learning best practices
Data strategy and governance
Data ethics and bias
Recommendation engines
Designing ML pipelines efficiently
Career paths
Hiring and Recruitment
Seeking mentorship with purpose
The importance of female-first spaces
Navigating male-dominated teams
Overcoming imposter syndrome
Data science teams: managing, building, collaboration
Integrating open source tools into your workflows
Data and AI for emerging platforms
Data governance

About DSSe

DSSe is an initiative to elevate and connect the voices of women in data science and encourage companies to set a better habit to generally consider women for data-intense roles.

DSSe is important because the field of Data Science is still young — for it to fulfill its true potential, we need voices that reflect the full experience of the world we live in to contextualize our data-derived insights.

By elevating women and other underrepresented groups, we have the opportunity to build a truly incredible and thriving field that influences decision-making at every level in a meaningful way.

Speakers

Lisa Burton O'Toole

Lisa Burton O'Toole

Executive Director at HearstLab

Jenifer Jones

Jenifer Jones

Executive Director, Enterprise Data Science at The Estée Lauder Companies Inc.

Teresa Borcuch

Teresa Borcuch

Sr Data Scientist at iRobot

Claudia Perlich

Claudia Perlich

Senior Data Scientist at Two Sigma

Friederike Schüür

Friederike Schüür

Director of Machine Learning & Research at CityBlock Health

Noemi Derzsy

Noemi Derzsy

Senior Inventive Scientist at AT&T Labs

Frida Polli

Frida Polli

Founder and CEO at Pymetrics

Marianne Hoogeveen

Marianne Hoogeveen

Staff Data Scientist at Bowery Farming

What people are saying

Having successful women to look up to as role models in data science is part of the solution to inspire more women to join the field.

Jessica Renaud

BI Analyst, Videotron

“DSSe is important because the field of Data Science is still young — for it to fulfill its true potential, we need voices that reflect the full experience of the world we live in to contextualize our data-derived insights.

By elevating women and other underrepresented groups, we have the opportunity to build a truly incredible and thriving field that influences decision-making at every level in a meaningful way.”

Amarita Natt

Sr. Economist, Econ One Research

DSSe provides a platform where women can exhibit their perspectives on leadership in data science and analytics. DSSe is providing this platform in the face of hundreds of thousands of new jobs being created in these fields over the next few years. In doing so, DSSe contributes to improving the diversity of thought and experience required for a thriving data science and analytics workforce.

Karen Bellin

VP Data and Analytics, Mirum Agency

Schedule

8.30AM – 9.25AM

Registration

9.25am - 9.30am

Opening remarks

Jeremy and Anna – FormulatedBy

9.30am - 10.00am

30 min talk

Lisa Burton O’Toole – Executive Director at HearstLab

Lisa Burton Ph.D. is the Executive Director of HearstLab, providing investment and resources for early-stage, women-led startups that innovate across media, data and technology. At the Lab, she identifies prospective startups to invest in and supports the portfolio companies in residence, including advising on data science and product.

Lisa built data science teams at multiple startups before founding AdMass, a startup that leveraged social media data to help brands understand and connect with their customers online. She holds a Ph.D. and master’s degree (S.M.) from MIT and B.S. from Duke, all in Mechanical Engineering. Lisa currently serves on the Advisory Board of Duke University’s Department of Mechanical Engineering and Materials Science.

9.30am - 10.00am

30 min talk

Lisa Burton O’Toole – Executive Director at HearstLab

Lisa Burton Ph.D. is the Executive Director of HearstLab, providing investment and resources for early-stage, women-led startups that innovate across media, data and technology. At the Lab, she identifies prospective startups to invest in and supports the portfolio companies in residence, including advising on data science and product.

Lisa built data science teams at multiple startups before founding AdMass, a startup that leveraged social media data to help brands understand and connect with their customers online. She holds a Ph.D. and master’s degree (S.M.) from MIT and B.S. from Duke, all in Mechanical Engineering. Lisa currently serves on the Advisory Board of Duke University’s Department of Mechanical Engineering and Materials Science.

10.00am - 10.30am

30 min talk

Jenifer Jones – Executive Director, Enterprise Data Science at The Estée Lauder Companies Inc.

10.30am - 10.50am

30 min talk

Speaker TBD

10.50AM – 11.10AM

Coffee Break & Networking

11.10am - 11.40am

Friederike Schüür – Director of Machine Learning & Research at CityBlock Health

30 min talk

Friederike Schüür  – Director of Machine Learning & Research at CityBlock Health

11.40am - 12.10pm

30 min talk

Teresa Borcuch – Sr Data Scientist at iRobot

12.10pm - 12.30pm

20 min talk

Noemi Derzsy – Senior Inventive Scientist at AT&T Labs

12.30pm - 1.00pm

30 min talk

Claudia Perlich – Senior Data Scientist at Two Sigma

1.00PM – 1.50PM

Lunch Break & Networking

1:50pm - 2:35pm

45 min panel

Panelists TBD

2:35pm - 3:05pm

30 min talk

Marianne Hoogeveen – Staff Data Scientist at Bowery Farming

3.05PM – 3.35PM

Coffee Break & Networking

3:35pm - 4:05PM

Monitoring System Alerts with Machine Learning

Manisha Verma – Research Scientist at VerizonMedia

Given that VerizonMedia hosts services that span thousands of machines, it is important to monitor the machines or individual services (for example databases or web servers) for failures and identify which components might be failing as fast as possible so the end-user is not affected. Our model aims to control the number of alerts that are sent out to software reliability engineers or folks at operation centers.

At the moment, we have a monitoring system, where people configure what they want to monitor (for example CPU memory, disk write/read failures) and alert the product/service owners about any discrepancies in the series listed in these configurations.

Our objective was to train and test several machine learning models to predict which alerts were important and what alerts to escalate to SREs and SEs for resolution. We use techniques from text mining and Hawkes processes to eventually build a classifier to label each alert. I want to give the audience an overview of how machine learning could yield improvements in monitoring thousands of machines and reduce engineer workload.
I will be discussing TensorFlow, sklearn, python and a library for Hawkes processes for this talk.

About the speaker

Manisha Verma is a Research Scientist in New York City. She completed Ph.D. in Computer Science from UCL, London. Her research interests are data mining, information retrieval with an emphasis on applying NLP and IR techniques to large scale alert noise management and time series retrieval for incident resolution across platforms. Some of her work has been published at conferences such as RecSys, CIKM, WSDM, ECIR and SIGIR.

4:05pm - 4:35PM

Different recommendation engine algorithms and their uses

Kiruthika Sankaran – Data Scientist at Key Me

The talk outlines what is a recommender system and where it is being used. What are the different algorithms that can be used to build better recommender engines? Using python to code and build the recommender engine and compare the performance between different algorithms. Choose the best algorithm based on the dataset and the algorithm’s performance on the dataset.

4:35PM - 5:05PM

30 min talk

Frida Polli – Founder and CEO Pymetrics

5:05PM - 5:25PM

30 min talk

Speaker TBD

5:25pm - 5:55PM

30 min talk

Speaker TBD

5:55pm - 6:00PM

Closing remarks

Formulatedby

6.00PM – 8.00PM

Networking Reception

Register now

Early Bird Ticket

Individual

$99

All sessions | Regular seating
Food included | Opening reception

media partners

DATE AND TIME

May 21, 2020

8:00 AM – 6:00 PM EST

 

LOCATION

TBD

New York

Get in touch: info@formulated.by (415) 322-0760

Get in touch:

 info@formulated.by  

(415) 322-0760