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Data Science New York

January 23-24, 2018, New York

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Conference Day 1
23 January
08:00

Registration & Networking in the Exhibition Area

Registration & Networking in the Exhibition Area

January 23 | 08:00 - 08:45

Speaking:

08:45

Chair’s Opening Remarks

Chair’s Opening Remarks

January 23 | 08:45 - 09:00

Speaking:

09:00

Turning Insights into Income - Growth Through Commercial Data Science

  • Using Data Science to effectively examine which pipelines are still profitable and which are not
  • Growing the market share by identifying weakness in both your firm and the competition
  • Looking at...

Speaking:

cary

Cary Correia

Chief Commercial Data Scientist, GE

Turning Insights into Income - Growth Through Commercial Data Science

January 23 | 09:00 - 09:30

  • Using Data Science to effectively examine which pipelines are still profitable and which are not
  • Growing the market share by identifying weakness in both your firm and the competition
  • Looking at alternative data: can you use public databases such as census data to understand where the enterprise should be investing more time and money?

Speaking:

cary

Cary Correia

GE

09:30

Why Big Data Efforts Are Failing to Deliver

  • Organizations lack of Big Data Foundations
  • Silos of knowledge
  • Lack of finding people with the right "BIG" skill sets
  • Tool and technology mismatch

Speaking:

Robert-Whetsel-230x230

Robert Whetsel

Chief Data Scientist, U.S. Department of Defense

Why Big Data Efforts Are Failing to Deliver

January 23 | 09:30 - 10:00

  • Organizations lack of Big Data Foundations
  • Silos of knowledge
  • Lack of finding people with the right "BIG" skill sets
  • Tool and technology mismatch

Speaking:

Robert-Whetsel-230x230

Robert Whetsel

U.S. Department of Defense

10:00

Customer Lifetime Value Optimization - Using AI, Machine Learning and Data Science

  • Historic CLV is old news! Forecasting a predictive CLV will see bottom line growth
  • What techniques are out there and which one applied to my business?
  • What about non-contractual business? Can...

Speaking:

Mukesh Dalal - Bose

Mukesh Dalal

Global Head of Data Science and Analaytics, Bose

Customer Lifetime Value Optimization - Using AI, Machine Learning and Data Science

January 23 | 10:00 - 10:30

  • Historic CLV is old news! Forecasting a predictive CLV will see bottom line growth
  • What techniques are out there and which one applied to my business?
  • What about non-contractual business? Can probabilistic models actually provide solid insight?

Speaking:

Mukesh Dalal - Bose

Mukesh Dalal

Bose

10:30

Panel Discussion: Customer Personalisation - Leveraging Data Science and Technology to Deliver an Optimised Customer Journey

  • Customers demand a personalized experience that delivers them value - organizations need to deliver this while optimizing their financial business metrics
  • With productized Data Science (data,...

Speaking:

Mark Wang

Mark Wang

Chief Data Scientist, Alorica

Sandeep-Kaul-Samsung-230x230

Sandeep Kaul

Head of Digital Analytics, Samsung Electronics America

Dan-Wulin-Wayfair-230x230

Dan Wulin

Director, Data Science, Wayfair

Carl Gold Zuora

Carl Gold

Chief Data Scientist, Zuora

Panel Discussion: Customer Personalisation - Leveraging Data Science and Technology to Deliver an Optimised Customer Journey

January 23 | 10:30 - 11:00

  • Customers demand a personalized experience that delivers them value - organizations need to deliver this while optimizing their financial business metrics
  • With productized Data Science (data, analytics, technology and product integration), this can be done at scale and at speed in many shapes and forms
  • The perception of value of 1-1 personalization can be affected by individual customer's perception of a company's leveraging "their data" in ways they find infringing on their privacy.
  • With GDPR, a customer can do more than just choose not to be a customer, they can demand you act – working with the customer is key

Speaking:

Dan-Wulin-Wayfair-230x230

Dan Wulin

Wayfair

Sandeep-Kaul-Samsung-230x230

Sandeep Kaul

Samsung Electronics America

Carl Gold Zuora

Carl Gold

Zuora

Mark Wang

Mark Wang

Alorica

11:00

Coffee & Networking in the Exhibition Area

Coffee & Networking in the Exhibition Area

January 23 | 11:00 - 11:30

Speaking:

11:30

Demystifying the Black Box Problem – Gaining Stakeholders’ Trust

  • Transparency is key to stakeholders and impossible to give in a black box environment: what are our options?
  • Do ‘pseudo-explanations’ help or hinder the trust process?
  • Stakeholders aren’t data...

Speaking:

Deepna Devkar

Deepna Devkar

VP, Head of Data Science, Dotdash

Demystifying the Black Box Problem – Gaining Stakeholders’ Trust

January 23 | 11:30 - 12:00

  • Transparency is key to stakeholders and impossible to give in a black box environment: what are our options?
  • Do ‘pseudo-explanations’ help or hinder the trust process?
  • Stakeholders aren’t data scientists – how do you develop storytelling skills for somethings as complex as Deep Learning?
  • How can we engage with stakeholders in a diplomatic, clear, and concise way to gain their trust and to help them understand these models?

Speaking:

Deepna Devkar

Deepna Devkar

Dotdash

12:00

How to Drive Institutional Change to Increase Profit & Productivity as a Data Science Leader

  • We all know the value of data science to an organization, but leading the drive for real institutional change is not as easy as it seems
  • This session will examine the techniques and pitfalls when...

Speaking:

Daniel Costanza

Daniel Costanza

Chief Data Scientist, Citi

How to Drive Institutional Change to Increase Profit & Productivity as a Data Science Leader

January 23 | 12:00 - 12:30

  • We all know the value of data science to an organization, but leading the drive for real institutional change is not as easy as it seems
  • This session will examine the techniques and pitfalls when using the data as a tool for widespread change
  • It will use real world examples and case studies to provide you with the tools you need to be the force for change at your company

Speaking:

Daniel Costanza

Daniel Costanza

Citi

12:30

Panel Discussion: How to Make Sure Your Synthetic Dataset Produces Usable Results

  • Privacy, data ownership, and data-hungry algorithms – synthetic datasets are becoming a major asset to any Chief Data Scientist
  • Synthetic datasets take time to build and are difficult to get right –...

Speaking:

Antonio Carbajal Turner

Antonio Carbajal

Vice President, Data Science, Turner (Turner Broadcasting System, Inc)

Sanji Fernando - UnitedHealthGroup

Sanji Fernando

Vice President, OptumLabs Center for Applied Data Science, UnitedHealth Group

Dipti Patel Misra

Dipti Patel-Misra

Chief Data & Analytics Officer, Vituity

Panel Discussion: How to Make Sure Your Synthetic Dataset Produces Usable Results

January 23 | 12:30 - 13:00

  • Privacy, data ownership, and data-hungry algorithms – synthetic datasets are becoming a major asset to any Chief Data Scientist
  • Synthetic datasets take time to build and are difficult to get right – what models are working in the real world?
  • Research and the future: will we ever see perfect synthetic datasets?

Speaking:

Dipti Patel Misra

Dipti Patel-Misra

Vituity

Sanji Fernando - UnitedHealthGroup

Sanji Fernando

UnitedHealth Group

Antonio Carbajal Turner

Antonio Carbajal

Turner (Turner Broadcasting System, Inc)

1:00

Lunch & Networking in the Exhibition Area

Lunch & Networking in the Exhibition Area

January 23 | 13:00 - 14:00

Speaking:

Track A | People

2:00

Discussion Group 1A: Hiring the Unicorn: What Makes a Great Data Scientist?

Speaking:

Philipp Diesinger

Philipp Diesinger

Global Chief Data Scientist, Boehringer Ingelheim

Deepna Devkar

Deepna Devkar

VP, Head of Data Science, Dotdash

Haftan-Eckholdt-Plated-230x230

Haftan Eckholdt

Chief Data Officer & Chief Data Science Officer, Understood.org

Discussion Group 1A: Hiring the Unicorn: What Makes a Great Data Scientist?

January 23 | 14:00 - 14:45

Speaking:

Haftan-Eckholdt-Plated-230x230

Haftan Eckholdt

Understood.org

Deepna Devkar

Deepna Devkar

Dotdash

Philipp Diesinger

Philipp Diesinger

Boehringer Ingelheim

Track B | Data Science Transformation

2:00

Discussion Group 1B: Data Science Advocacy: Educating and Working with the Business Stakeholders

Speaking:

Rajeeve-Kaul

Rajeeve Kaul

Global Chief Pricing Officer, McDonald's

Mike-Berges-230x230

Mike Berger

VP, Pop Health Informatics and Data Science, Mount Sinai Health System

Thomas-Vincent-Getty-Images-230x230

Thomas Vincent

Head of Data Science, Getty Images

Discussion Group 1B: Data Science Advocacy: Educating and Working with the Business Stakeholders

January 23 | 14:00 - 14:45

Speaking:

Thomas-Vincent-Getty-Images-230x230

Thomas Vincent

Getty Images

Rajeeve-Kaul

Rajeeve Kaul

McDonald's

Mike-Berges-230x230

Mike Berger

Mount Sinai Health System

Track C | Law and Ethics

2:00

Discussion Group 1C: Discrimination and Privacy - What are the Key Legal and Ethical Considerations for the Chief Data Scientist?

Speaking:

Bennett Borden - DBR

Bennett Borden

Chief Data Scientist, Drinker Biddle & Reath LLP

Edmund-Jackson-HCA-230x230

Edmund Jackson

VP & Chief Data Scientist, Hospital Coporation of America (HCA)

Discussion Group 1C: Discrimination and Privacy - What are the Key Legal and Ethical Considerations for the Chief Data Scientist?

January 23 | 14:00 - 14:45

Speaking:

Edmund-Jackson-HCA-230x230

Edmund Jackson

Hospital Coporation of America (HCA)

Bennett Borden - DBR

Bennett Borden

Drinker Biddle & Reath LLP

Track A | People

2:45

Discussion Group 2A: Retaining, Growing & Feeding: Ensuring Your Best Stay

Speaking:

Dipti Patel Misra

Dipti Patel-Misra

Chief Data & Analytics Officer, Vituity

Victor-Lo-Fidelity-230x230

Victor Lo

Head of Data Science and Artificial Intelligence, Workplace Solutions, Fidelity Investments

Mukesh Dalal - Bose

Mukesh Dalal

Global Head of Data Science and Analaytics, Bose

Discussion Group 2A: Retaining, Growing & Feeding: Ensuring Your Best Stay

January 23 | 14:45 - 15:30

Speaking:

Dipti Patel Misra

Dipti Patel-Misra

Vituity

Mukesh Dalal - Bose

Mukesh Dalal

Bose

Victor-Lo-Fidelity-230x230

Victor Lo

Fidelity Investments

Track B | Data Science Transformation

2:45

Discussion Group 2B: Transforming Traditional Industries into Data Science Champions

Speaking:

John Behrens - Pearson

John Behrens

VP, Advanced Computing and Data Science Lab , Pearson

BNSF

Pooja Dewan

Chief Data Scientist, BNSF Railway

Discussion Group 2B: Transforming Traditional Industries into Data Science Champions

January 23 | 14:45 - 15:30

Speaking:

BNSF

Pooja Dewan

BNSF Railway

John Behrens - Pearson

John Behrens

Pearson

Track C | Law and Ethics

2:45

Discussion Group 2C: Data Science’s Impact on the Workforce - Job Loss, Creation and Evolution

Speaking:

Sachin-Ahuja-CNH-Industrial-230x230

Sachin Ahuja

Chief Data Scientist and Global Director, CNH Industrial

Rajeeve-Kaul

Rajeeve Kaul

Global Chief Pricing Officer, McDonald's

Discussion Group 2C: Data Science’s Impact on the Workforce - Job Loss, Creation and Evolution

January 23 | 14:45 - 15:30

Speaking:

Sachin-Ahuja-CNH-Industrial-230x230

Sachin Ahuja

CNH Industrial

Rajeeve-Kaul

Rajeeve Kaul

McDonald's

3:30

Coffee & Networking in the Exhibition Area

Coffee & Networking in the Exhibition Area

January 23 | 15:30 - 16:00

Speaking:

4:00

Building the Homo Deus – How Augmenting Workers with AI Will Lead to a More Productive Workforce

  • The enormous effort devoted to developing “artificial intelligence” that mimics human decision-making may be misplaced and even counterproductive for many organizations.
  • For knowledge work, in...

Speaking:

Michael Simon

Michael Simon

Chief of Analytics, Central Intelligence Agency (CIA)

Building the Homo Deus – How Augmenting Workers with AI Will Lead to a More Productive Workforce

January 23 | 16:00 - 16:30

  • The enormous effort devoted to developing “artificial intelligence” that mimics human decision-making may be misplaced and even counterproductive for many organizations.
  • For knowledge work, in particular, we should not strive for AI systems to replace humans, since we run the risk of reifying the cognitive and organizational biases that already exist.
  • Instead, we should harness the power of computers to perform tasks that human experts are not very good at accomplishing (such as situational awareness), leaving more time in the workday for human experts to do what they are good at (thinking creatively and identifying causal relationships).
  • By building joint human-machine platforms, we can efficiently share knowledge across an organization and prioritize what additional information to collect.
  • This approach can also ease the transition from today’s workplace to a future one, by starting with expertise-driven causal explanations and by requiring AI methods to be understandable.

In addition to describing a future workflow in which we leverage the best of human and machine intelligence, this presentation also points out the challenges in moving to this future. Specifically, the presenter will discuss key technical and cultural gaps that will need to be overcome if we are to get greater value out of the data we possess and collect and to enable data-driven decision-making at scale. These gaps represent priority areas for research funding, which business leaders should support.

Speaking:

Michael Simon

Michael Simon

Central Intelligence Agency (CIA)

4:30

Using AI to Enhance Journalism

  • Case Study: Forbes' AI Content Publishing System
  • Examining real-world use case highlighting the potential of AI-powered tools to improve how news are written and distributed
  • Learn about Forbes’ new...

Speaking:

Luis-Capelo-Forbes-230x230

Luis Capelo

Head of Data Products, Forbes

Using AI to Enhance Journalism

January 23 | 16:30 - 17:00

  • Case Study: Forbes' AI Content Publishing System
  • Examining real-world use case highlighting the potential of AI-powered tools to improve how news are written and distributed
  • Learn about Forbes’ new Artificially Intelligent publishing platform, Bertie, and how it is used by our staff as an intelligent assistant

Speaking:

Luis-Capelo-Forbes-230x230

Luis Capelo

Forbes

5:00

Panel Discussion: Writing the Trust Contract – How Do You Help Foster Trust in the Data Science Process and its Results?

  • While most enterprise leaders view data science as an integral part of the modern business, forming a trust contract is still an incredibly difficult task
  • How do we overcome the mistrust in both the...

Speaking:

John Mercer

John Mercer

Head of Data Science, Pixability

0-230x230

Tom Hamilton

VP, Head of Analytics Center of Excellence, Voya Financial

Sriram-Subramanian-Conde-nast-230x230

Sriram Subramanian

Head of Data Science, Condé Nast

Sachin-Ahuja-CNH-Industrial-230x230

Sachin Ahuja

Chief Data Scientist and Global Director, CNH Industrial

Subhashini-Tripuraneni-7eleven-230x230

Subhashini Tripuraneni

Head of Data Science & Head of Artificial Intelligence, 7-Eleven

Panel Discussion: Writing the Trust Contract – How Do You Help Foster Trust in the Data Science Process and its Results?

January 23 | 17:00 - 17:30

  • While most enterprise leaders view data science as an integral part of the modern business, forming a trust contract is still an incredibly difficult task
  • How do we overcome the mistrust in both the complex process and the fact data science is often iterative?
  • What can we do to make sure business leader’s understand data science’s value beyond the “magic wand” projects?

Speaking:

Subhashini-Tripuraneni-7eleven-230x230

Subhashini Tripuraneni

7-Eleven

Sachin-Ahuja-CNH-Industrial-230x230

Sachin Ahuja

CNH Industrial

Sriram-Subramanian-Conde-nast-230x230

Sriram Subramanian

Condé Nast

0-230x230

Tom Hamilton

Voya Financial

John Mercer

John Mercer

Pixability

5:30

Chair’s Closing Remarks

Chair’s Closing Remarks

January 23 | 17:30 - 17:45

Speaking:

5:45

Drinks Reception & Networking in the Exhibition Area

Drinks Reception & Networking in the Exhibition Area

January 23 | 17:45 - 18:45

Speaking:

6:45

End of Main Conference

End of Main Conference

January 23 | 18:45

Speaking:

Conference Day 2
24 January
08:30

Registration, Coffee & Networking in the Exhibition Area

Registration, Coffee & Networking in the Exhibition Area

January 24 | 08:30 - 08:45

Speaking:

08:45

Chair’s Opening Remarks

Chair’s Opening Remarks

January 24 | 08:45 - 09:00

Speaking:

09:00

Predicting and Preventing Payment Fraud Through Data Science

  • Businesses lose more than $3.5 trillion to fraud each year, a massive and systematic drain on profit – how can Data Science reduce these loses?
  • Classic machine learning techniques can suffer from low...

Speaking:

Eric Nyabiosi - Comcast

Eric Nyabiosi

VP - Head of AI ML Predictive Modeling, Comcast

Predicting and Preventing Payment Fraud Through Data Science

January 24 | 09:00 - 09:30

  • Businesses lose more than $3.5 trillion to fraud each year, a massive and systematic drain on profit – how can Data Science reduce these loses?
  • Classic machine learning techniques can suffer from low fraud detection rates and a massive amount of false positives – what alternatives are there and how can we optimize the process?
  • Case study: Exploring a real-time, scalable fraud detection solution

Speaking:

Eric Nyabiosi - Comcast

Eric Nyabiosi

Comcast

09:30

Panel Discussion: Shrinking the Haystack - Combatting Fraud and Insider Threat with Advanced Monitoring Solutions for High Fidelity Alerts

  • Insider threat is a very small proportion of employee behaviour, so how can we help our models to differentiate between legitimate access and illegal activity?
  • Can cognitive computing shrink the...

Speaking:

Joel Amick-TIAA-1

Joel Amick

Director, Cyber Analytics and Data Science, TIAA

Sears Mettiyy - MassMutual-1

Sears Merritt

Chief Data Scientist, MassMutual Financial Group

Panel Discussion: Shrinking the Haystack - Combatting Fraud and Insider Threat with Advanced Monitoring Solutions for High Fidelity Alerts

January 24 | 09:30 - 10:00

  • Insider threat is a very small proportion of employee behaviour, so how can we help our models to differentiate between legitimate access and illegal activity?
  • Can cognitive computing shrink the haystack to identify insider threat and fraud in real time?
  • Different techniques used to improve the detection rates and filter out the noise of false positives at scale

Speaking:

Sears Mettiyy - MassMutual-1

Sears Merritt

MassMutual Financial Group

Joel Amick-TIAA-1

Joel Amick

TIAA

10:00

Coffee & Networking in the Exhibition Area

Coffee & Networking in the Exhibition Area

January 24 | 10:00 - 10:30

Speaking:

Track A | Data

10:30

Discussion Group 3A: What Are The Most Effective Strategies For Scaling Your Data Science Infrastructure?

Speaking:

Antonio Carbajal Turner

Antonio Carbajal

Vice President, Data Science, Turner (Turner Broadcasting System, Inc)

Subhashini-Tripuraneni-7eleven-230x230

Subhashini Tripuraneni

Head of Data Science & Head of Artificial Intelligence, 7-Eleven

jeff_bx_headshot-230x230

Jeffrey Sternberg

SVP, Data Science Engineering, The Blackstone Group

Discussion Group 3A: What Are The Most Effective Strategies For Scaling Your Data Science Infrastructure?

January 24 | 10:30 - 11:15

Speaking:

Subhashini-Tripuraneni-7eleven-230x230

Subhashini Tripuraneni

7-Eleven

jeff_bx_headshot-230x230

Jeffrey Sternberg

The Blackstone Group

Antonio Carbajal Turner

Antonio Carbajal

Turner (Turner Broadcasting System, Inc)

Track B | Building the Data Science Team

10:30

Discussion Group 3B: How Do You Prevent Group Think in a Data Science Team?

Speaking:

Sears Mettiyy - MassMutual-1

Sears Merritt

Chief Data Scientist, MassMutual Financial Group

Carl Gold Zuora

Carl Gold

Chief Data Scientist, Zuora

John Mercer

John Mercer

Head of Data Science, Pixability

Discussion Group 3B: How Do You Prevent Group Think in a Data Science Team?

January 24 | 10:30 - 11:15

Speaking:

Sears Mettiyy - MassMutual-1

Sears Merritt

MassMutual Financial Group