THURSDAY, June 18 @ 12:30 PM – 4:30 PM EDT

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Speakers include

Christina Echagarruga

Christina Echagarruga

Data Scientist at Scribd

Sarah Koehler

Sarah Koehler

Data Scientist at Scribd

Dhivya Rajprasad

Dhivya Rajprasad

Lead Data Scientist at Levi Strauss & Co.

Gabriela de Queiroz

Gabriela de Queiroz

Sr. Machine Learning Manager at IBM

Kay Sin

Kay Sin

Technical Program Manager at LinkedIn

Teresa Borcuch

Teresa Borcuch

Sr Data Scientist at iRobot

Jing Sang

Jing Sang

Analytics Manager at Dropbox

Deborah Berebichez

Deborah Berebichez

Chief Data Scientist at Metis

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.


12:30pm - 12:40pm


12:40pm - 1:10pm

Beyond “Fizz-Buzz”: Coding Challenges for Hiring Data Scientists

Teresa Borcuch – Sr Data Scientist at iRobot

For hiring software engineers, coding challenges can take many forms, ranging from quick brain teasers to writing hundreds of lines of code. The goal is to determine whether or not a candidate has the technical ability to perform in the role they are applying to. I have also found coding challenges to be valuable when assessing prospective data science hires’ programming, analytical, and communication skills – some of the keys to success in a data science role. In this talk, I will describe some of the pros and cons of using coding challenges in the hiring process for data scientists, how I designed one, and how it evolved with the needs and responsibilities of the team.

1:15pm - 1:45pm

Deep Learning for Everyone

Gabriela de Queiroz – Sr. Machine Learning Manager at IBM

As a Data Scientist (or aspiring Data Scientist) we are overwhelmed by the amount of knowledge we need to have and acquire. Every day there is a new technique, a new framework, a new state of the art model. For the last few years, Deep Learning has become a hot topic and it is the main driver of many applications. But how can we start our Deep Learning journey? Which of the several deep learning frameworks should we use? Where can I find examples of code that work and that I can use without worrying about the license?

In this talk, I will show you how you can start with Deep Learning without any previous Deep Learning knowledge and how you can have a basic ready-to-use deep learning “service” running in less than five minutes.

1:50pm - 2:20pm

Don’t Fake it, Own it: Facing Early Career Imposter Syndrome

Kay Sin – Technical Program Manager at LinkedIn

Persistent self-doubt can go hand in hand with an insatiable need to prove one’s competence—or rather, to disprove one’s incompetence. Because early career experiences can influence one’s attitude towards future opportunities, it is critical to break the cyclical thoughts that can lead to an unhealthy work/life balance and a loss of sense of self. This dialogue aims to share the methods that I have employed to build stronger self-awareness, interpret situations more constructively, and restructure how I spend my time to gain confidence and support. Attendees in similarly early career stages will better understand the source of their imposter syndrome and learn the possible paths forward. Attendees in more mature career stages will be able to reflect on their past experiences to share tips and advice that they have found to be effective.

2:35pm - 3:05pm

Hacking p-Hacking: Avoiding Spurious Analyses with Automation

Sarah Koehler – Data Scientist at Scribd

Christina Echagarruga – Data Scientist at Scribd

Obtaining spurious results on hypothesis tests is a significant risk for analysts and business users when tools and methods are easy to accidentally or intentionally misuse. We cover two scenarios where these errors are common: multiple comparisons and sample size estimation. We will discuss the pitfalls in the currently available tools, how they affect your results, and how you can build solutions to help users avoid them.

3:10pm - 3:40pm

Real time, contextual and personalized recommendations

Dhivya Rajprasad – Lead Data Scientist at Levi Strauss & Co.

Levi Strauss and Co has always been at the helm of innovation with their classic denims and seasonal takes on the future of denim . We would like to enable users who visit our website, receive our emails and visit our stores to have the most personalized experience with easier product discovery. To enable this, I have built recommendation systems based on live and past user behavior and with minimal infrastructure.

The talk would feature two main areas:

  • How to work with minimal data , implicit feedback and business to build recommender systems that satisfy users needs while keeping in mind overarching business KPIs
  • How to use real stream of events and past indications to give a completely personalized experience that can keep updating based on user interaction with minimal architectural requirements.

3:45pm - 4:05pm

How to Thrive Regardless of Background and Limited Resources

Jing Sang – Analytics Manager at Dropbox

How mindset, execution and adaptability play a critical role in achieving goals in life, professionally and personally.

4:10pm - 4:40pm

How Data Science Can Empower Your Business

Deborah Berebichez – Chief Data Scientist at Metis

Most people are unaware of a fundamental truth: everyone uses data to analyze the world. This truth is like the atmosphere: all around us, essential for life and yet invisible, so few people recognize it. A pity, because if more companies understood this truth, it would improve every aspect of their business. Deborah Berebichez, Chief Data Scientist at Metis, explains in non-technical language why it is important to create business environments where everyone contributes to and learns from the company’s data and how people and data can work together for better business.

4:40pm - 5:00pm

Wrap up


DSS Elevate is a non-profit event. Your ticket covers our production fees so we can continue to elevate women and other underrepresented groups.

For any queries regarding Registration or Tickets, please contact us via info@formulated.by 

Coffee chat @ 12pm the next day

Join us for a cup of coffee or tea and a chat the morning after the DSS Elevate Virtual Conference.

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