DSSVirtual @ Transform World

July 12, 2021 | virtual event

Sponsored by

We are excited to announce that we’ll join forces with Venture Beat for their Transform 2021, one of the most important events of the year for enterprise technical leaders on how to implement applied AI.

The Data Science Salon will be hosting the data science in the enterprise track at the conference, covering state-of-the art AI and machine learning applications in some of the hottest industries, including finance, retail, healthcare, media, advertising & entertainment.


Yuling Ma

Yuling Ma

Chief Technology Officer at FreeWheel

June Andrews

June Andrews

Data Science Manager of Style Discovery at Nike

Vijay Pappu

Vijay Pappu

Senior Machine Learning Engineer at Peloton

Tim Yoo

Tim Yoo

Sr. Director, Head of Analytics at Roku Inc

Rochelle March

Rochelle March

Head of ESG Product at Dun & Bradstreet

Sriram Subramanian

Sriram Subramanian

Head of Data Science & Engineering at Condé Nast

Laura Gabrysiak

Laura Gabrysiak

Data Science Manager at Visa

Saira Kazmi

Saira Kazmi

Enterprise Data Strategy and Engineering at CVS Health

Appu Shaji

Appu Shaji

CEO & Founder at Mobius Labs

Reed Peterson

Reed Peterson

Field CTO - Telecom Strategy at Data Stax


The data science salon is a unique vertical focused conference which grew into a diverse community of senior data science, machine learning and other technical specialists. We gather face-to-face and virtually to educate each other, illuminate best practices and innovate new solutions in a casual atmosphere.


11.30AM – 11.40AM

Introduction & Housekeeping

11.40am - 12.10pm

30 min talk

Yuling Ma – Senior Vice President of Engineering at FreeWheel

12.15pm - 12.45pm

Considerations for Successful Model Management

Saira Kazmi Enterprise Data Strategy and Engineering at CVS Health

AI/ML is top of mind for leaders across academia and the industry. Many have tried and failed several times before successfully deploying models that bring real business value or have an impact. Even after a model is deployed, constant maintenance and monitoring is required to ensure that the model is relevant and makes good decisions that are still applicable to the changing business environment. Key factors leading to successful deployments include: * Availability and maturity of data to build a model and availability of this data when making real-time decisions * Thorough understanding of the business problem * Understanding of nuances leading to data variability * We can often overestimate what models can do – a simple test “Is the Candidate task simple for a human to solve?” can help. * Automation will lead to ROI (the problem is large enough to automate) * Mechanisms are in place to track the algorithm performance * There is a way to provide feedback on the solution and model decisions * The model is kept alive (refreshed with new data at regular intervals


12.50pm - 1.20pm

30 min talk

1.25pm - 1.55pm

30 min talk

June Andrews – Data Science Manager of Style Discovery at Stitch Fix

2.00pm - 2.30pm

30 min talk

Vijay Pappu – Senior Machine Learning Engineer at Spotify

2.35pm - 3.05pm

30 min talk

Vijay Pappu – Senior Machine Learning Engineer at Spotify

3.10pm - 3.40pm

Using Data to Optimize the Content Acquisition Lifecycle

Tim Yoo – Sr. Director, Head of Analytics at Roku Inc


The content acquisition lifecycle is complex and multi-faceted. Streaming services that strive to be both a competitive service and a meaningful source of entertainment to consumers need to efficiently value content as well as understand the complex relationship between value to the company and to consumers. Discover how analytics and modeling can be used to navigate through the various stages of the content acquisition lifecycle.

3.45pm - 4.15pm

ESG as the signal in the noise: Using NLP and verified data assets to create a holistic measure of company resiliency

Rochelle March – Head of ESG Innovation and Analytics at Dun & Bradstreet


Global changes have impacted countries and companies everywhere. From climate change, the Covid-19 pandemic, resource constraints and demographic fluctuations challenge the stability of even the longest-established enterprises. Traditional financial data is not enough today to provide a clear enough picture on sourcing, investment and insurance decisions. ESG data and metrics can serve as valued information and tools for competitive advantage. For Dun & Bradstreet, this means extending its efforts around business transparency to generate ESG intel that can help customers, investors and other stakeholders identify which companies are actively moving towards a different, and hopefully, more sustainable future. This presentation will showcase analysis that explores the relationship between ESG and financial performance, and will provide a deep dive into the NLP machine learning and analytical techniques used to create Dun & Bradstreet’s new ESG Rankings dataset and model.

4.20pm - 4.50pm

30 min talk

Sriram Subramanian – Head of Data Science & Engineering at Condé Nast

4.55pm - 5.25pm

30 min talk

Laura Gabrysiak – Data Science Manager at Visa


Don’t see the registration form? Alternatively you can complete your registration here.

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



Putting ML Apps Into Production

Personalization At Scale With AI

Cloud Automation And Machine Learning

Natural Language Processing & Deep Learning

Engineering For Data Science

Scaling ML Production

Improving Data Quality

Machine Learning Best Practices

Data Strategy And Governance

Data Ethics And Bias

Recommendation Engines

Designing ML Pipelines Efficiently

Deep Neural Networks

Image Recognition With ML

Using Large Scale Data Sets

Data Science Teams: Managing, Building, Collaboration

Integrating Open Source Tools Into Your Workflows

Content Personalization And Monetization

Data And AI For Emerging Platforms

Data Governance And More!