Lessons in Building AI for Retail & Marketing: From Development to Deployment

During this discussion, the panelists will touch upon their successes, failures, tips & tricks from both a technical and business perspective on how to develop, deploy and strategize the implementation of AI.

Topics explored include:

- Strategy; how to best build AI to accurately solve business problems/needs
- Why AI projects fail, how we can overcome these common challenges
- Data: labeling, data science, sources
- Experiences/Challenges in managing data flows, pipelines
- Experiences/Challenges in managing knowledge flows: building cross-functional teams/ documenting work from a technical perspective
- Building teams & managing workflows from a managerial strategy/innovation perspective
- Holistic picture of the dev/deploy lifecycle/workflow & matching this to business needs
- The practicalities of implementing AI solutions
- Matching strategy to end goals & monitoring success
- Reproducibility of results, model accuracy
- AI/ML at scale
- Responsible/Ethical AI - strategies, design, accountability, explainability
- Building & deploying AI to foster customer engagement with the end product/service

Mari Joller, Founder & CEO at Snackable AI

Mari Joller is the Founder and CEO of Snackable AI, content discovery engine for the audio-first world. For the past six years, she has been in the trenches driving AI-based startups, observing first hand the psychology of how people interact with machines and its impact on designing AI-powered products.
 Before Snackable, Mari successfully founded and sold her company Scarlet, a cloud platform for delivering personal and branded content to the emerging audio ecosystem. Prior to Scarlet she co-founded Snazz, software for powering live events for businesses and brands. She previously built and scaled products at Virgin Mobile and Nokia.

Wariya Erez, Senior Data Scientist at Home Depot

Wariya Erez is a Principal Data Scientist with Home Depot Online where she is building large-scale personalized recommendation systems to help customers discover the best products and content at the right time on any digital touchpoint. Prior to Home Depot, Wariya was the Director of Data Services at Moxie - a digital-first advertising and CRM agency - where she led the analytics and data platform to help Fortune 500 clients such as Best Buy and OfficeMax to develop data-driven loyalty programs. Wariya earned her MS at Stanford University and BS at the University of Tokyo. She loves traveling and had visited over 40 countries.

Victor Morón Tejero, Lead Data Scientist at Nectar360

Victor Moron is a Data Scientist at Nectar Loyalty. With a PhD in theoretical and computational chemistry, Victor has always been interested in modelling and simulating processes that could not be understood otherwise. At Nectar, he leads a recently created Data Science team developing projects for personalisation, targeting and recommendation systems to improve the way customers are approached. The goal is to increase loyalty and cut the gap between proximity and new ways of shopping. Victor has previous experience in companies involved in understanding customer´s behaviour like Dunham, owner of Tesco club card or Abaka, a start-up nudging its users to take financially healthy decisions.

Shahmeer Mirza, Director of Technology at 7-Eleven

Shahmeer Mirza is the Director of Technology at 7Next, the R&D Division of 7-Eleven. Over the last several months he has led the team developing 7-Eleven’s Checkout-Free technology. In November of 2019, the team opened their first store at 7-Eleven’s headquarters, a culmination of their work in computer vision, machine learning, algorithms, distributed computing, and hardware engineering. He was previously at PepsiCo, where he developed next generation automation, computer vision, and machine learning solutions for Industry 4.0 applications. Shahmeer is also passionate about democratizing AI capabilities; while at PepsiCo, he created the first in a series of Data Analytics courses to upskill associates across the Snacks R&D organization. He holds a B.S. in Chemical and Biomolecular Engineering from Georgia Tech, and is currently pursuing his M.S. in Computer Science at Georgia Tech.

Hélio Pais, Data Science Manager at Trivago

I have been a Data Scientist at trivago for five years and I currently lead the Data Scientists at the marketplace department. In this function I support the development of data products that enable our advertisers to optimise their marketing campaigns at trivago. I studied Computer Science in the University of Lisbon and got a PhD in Computational Biology from the University of East Anglia. Before joining trivago I worked at the University of Oxford, where I applied computational methods in cancer research.

Cookies help us deliver our services. By using our services, you agree to our use of cookies. Learn more