August 14-15 | 
Boston, MA

Day One
Tuesday, August 14 2018

Day Two
Wednesday, August 15 2018

Chair’s Opening Remarks

  • Kevin Troyanos SVP Analytics & Data Science, Saatchi & Saatchi Wellness

Opening Keynote: From Science to Leadership


• What are the critical traits needed to be a successful data science leader?

• Demystifying the responsibilities of this nascent role

• Harmonizing scientific and business leadership styles – what are the critical components required from each?

• Building trust and support from the rest of the business as a data science leader

• How can we make data science truly successful?

Leadership, Culture & Business Engagement

Transforming Organizations Through Data Science


• Showing the transformative impact that data science can have on an organization that is not traditionally data-driven
• Understanding how the foundations of a business can be remodeled towards a data-centric approach
• What real value can data science add to a business to take success to the next level?
• How IP developed internally can be applied more broadly across the industry to capitalize on benefits at scale



Panel Discussion – Aligning Data Science with Business Culture


• Reorienting culture and traditional ways of practice to become more data driven
• Engaging senior and middle leadership to learn from technology through a new and unfamiliar approach
• From buzz word to practicality – changing perspectives on machine learning and data science to go beyond the surface level understanding of its capabilities
• Embedding data science into the strategic core of the company so it becomes intrinsic to every day business


Morning Refreshments & Speed Networking


This Speed Networking session is the ideal opportunity to meet face-to-face with other data science leaders. Specifically designed to connect you with many new contacts, take this opportunity to share learning, strategies and insight, as well as enhance your connections.


Business Use Case: Big Data enables advanced analytics and real-time applications


Data Science, which traces its origins to small data and simple algorithms has benefitted greatly from breakthroughs in big data processing.  Enterprises today have new opportunities to derive insights from terabytes of data, increasingly in real-time. Big data technologies, coupled with advances in AI and analytics is enabling enterprises to participate in the digital transformation revolution and truly achieve data-driven decision making at low cost. While we still face some challenges with data management, security and governance, advances in storage and compute through cloud offerings continue to accelerate data science adoption across all industries.

Learn how Impetus have married big data technologies and data science in deep learning and GPUs for industrial applications, and generation of personalized recommendations based on a Customer 360 degree view.  Explore how these capabilities are also being enabled for real-time applications through advanced analytics on a streaming analytics platform.


Panel Discussion – Business Ownership of Data Science Within the Corporate Structure


• Who should be involved in leading the initiative of data science?
• Comparing and contrasting reporting lines for data science: Data, IT, Finance, other
• Establishing partnerships and collaboration across all necessary teams
• Protecting and insulating data science teams – is this the best approach?
• How should reporting change as the data science team matures? What works for teams from start-up through to maturity?



People, Talent & Teams

Leadership Story – Managing Global Data Science Teams


Hear from L’Oreal’s leader who manages a global data science team to learn tips and strategies for taking your function to the next level. This session will discuss how he has managed offices working with different datasets in different languages and share insight into how to deal with teams who have competing objectives.


Panel Discussion – Designing, Structuring, Organizing & Growing a Team


• Reviewing the ideal mix of players and core competencies required in the team: Engineers vs Modellers vs Hackers vs Statisticians
• Matching team design with recruitment reality: experience, qualification, academic background
• Aligning team design with the wider business roles and capabilities
• Exploring when and how to scale to remain agile as business requirements change


Afternoon Refreshments & Networking

Audience Discussion – Recruitment & Retention in a Competitive Talent Market


• Competing with tech and data companies to make you stand out against the rest
• Balancing reward vs profitability: how to find people who are also cost effective
• Recruiting entry-level people and training them up: when is this the best option?
• Practical steps to working with universities to source junior talent
• Brainstorming the most effective techniques for keeping your team engaged
• Building diversity into your recruitment programme – racial diversity, gender diversity, background diversity




This session will break out into sector-specific roundtables to discuss particular industry questions and challenges around different data science initiatives.


Closing Remarks

  • Kevin Troyanos SVP Analytics & Data Science, Saatchi & Saatchi Wellness

End of Day One