Data Scientist
Data Scientist
Warner Bros. Entertainment
Combines descriptive and inferential statistics in order to have a holistic understanding of the data in order to fit the best models to the data. Has a Bachelor of Science in Statistics from the University of California, Los Angeles and pursuing Masters of Applied Statistics with strong foundation in statistics applied knowledge in capstone courses in multiple disciplines. Continues to grow statistics portfolio in the Work Force Analytics group in Warner Brothers.
Head of Business Development
Head of Business Development
NASA AMES Robotics Lab
Mc Kenna grew up in the heart of the silicon valley allowing her to be one of the original digital natives, giving an unusual perspective and relationship to technology. After finishing college in 2.5 years with a degree in economic policy, she went to work for a Private Equity REIT based in Latin America eventually running their business development. During that time she moved back to the Bay Area and started to help run the NASA AMES Robotics Lab, as the #1 robotics education program in the world the focus was about setting the example of what was possible and finding ways to help make those resources scalable to students around the world. She returned to the tech world full time when she started working for Tim Draper, helping with his Draper University program and as a partner at a seed investment fund where he was the primary LP. While working for Tim, she got heavily involved in the "Crypto" space, focusing on the applications of Blockchain, rather than the speculative asset class. Her writings on Venture Captial and technology have been published in Forbes, Adweek, and I.N.C, as well as being one of the top writers on Quora. More recently she was a co-founder of an AI company with a focus on creating tools to empower creatives to tell dynamic narratives. Currently, she is the Head of Business Development for VentureDevs and consults and advises for both startups and investment groups.
Data Scientist
Data Scientist
Latham & Watkins
There is an interesting story behind all data. Whether it be sports, education, etc. I'm always looking to find the meaning behind the numbers. Analyze, visualize, and explain what is going on behind the scenes. It's always been a passion of mine to find the unique answers to a puzzle with multiple solutions. Using data I've been able to find those unique answers that many may have overlooked in order to improve business efficiency.
My specialties include using a broad spectrum of software programs , advanced statistics, and an acumen for problem solving to find the answers buried in a company's data. I am currently an analyst at an E-Commerce Company and plan to enter the field of Machine Learning and Data Science.
Assistant Professor
Assistant Professor
University of California
Jingyi Jessica Li is an Assistant Professor in the Department of Statistics and the Department of Human Genetics at University of California, Los Angeles (UCLA). She is also a faculty member in the Interdepartmental Ph.D. Program in Bioinformatics and a member in the Jonsson Comprehensive Cancer Center (JCCC) Gene Regulation Research Program Area. Prior to joining UCLA in 2013, Jessica obtained her Ph.D. degree from the Interdepartmental Group in Biostatistics at University of California, Berkeley. Jessica received her B.S. (summa cum laude) from the Department of Biological Sciences and Technology at Tsinghua University, China in 2007. Jessica and her students focus on developing statistical and computational methods motivated by important questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, her research interests include association measures, high-dimensional variable selection, and classification metrics. On the biomedical application side, her research interests include next-generation RNA sequencing, comparative genomics, and information flow in the central dogma. Jessica is the recipient of the Hellman Fellowship (2015), the PhRMA Foundation Research Starter Grant in Informatics (2017), the Alfred P. Sloan Research Fellowship (2018), and the Johnson & Johnson WiSTEM2D Math Scholar Award (2018).
Developer Advocate
Developer Advocate
IBM
Before becoming an AI Advocate at IBM, Nick studied computer science at Purdue University and the University of Southern California, and was a high performance computing consultant for Hewlett-Packard in Grenoble, France. He now specializes in machine learning and interacting with other data scientists of various communities, startups, and enterprises in order to help them succeed on IBM’s data science platform. He has a strong interest in data science education and all things Kardashian.
Data Architect
Data Architect
Louis Sapia is a Data Architect who designs, develops and implements data analytics solutions that provide actionable insights to reduce costs, improve outcomes and provide forecasting models that lead to improved business performance. Louis provides expertise in various roles including data modeling, application design and development, data integration and visualization.
In addition to his career as a Data Architect, Louis teaches database technologies at universities and colleges including the University of Connecticut, Central Connecticut State University and, currently, Hillsborough Community College in Tampa Florida. Also, Louis provides training in SQL for corporate businesses.
Relational databases are the most common platform for data storage and the SQL language is used to communicate work with the data. This session will explain the importance of relational databases for structural storage of data and using SQL to retrieve it.
Data Architect
Data Science
Rajesh has over seven years of experience applying ML solutions on a wide set of problems in the tech industry. He started his career at ZS Associates, a management consulting company, and then went on to work for Google, Amazon, and Microsoft to build world-class ML enabled products. He was a co-founder of a Tech startup that was featured in Geekwire in 2015. Rajesh holds a Masters from the University of Wisconsin-Madison.
Data Scientist
Data Science
I graduated from Carnegie Mellon with a degree in Machine Learning, where I was fortunate to research under some of the world\'s leading Statisticians. I then completed a Masters from the Institute for Advanced Analytics (North Carolina), while simultaneously working with one of the world\'s last retirement funds (Putnam Investments), to accelerate their goal of becoming an AI-driven organization.\r\nFollowing that, I worked at Chewy.com for a little less than a year where I lead their Demand Forecasting efforts to establish labor plans for 8,000 employees, saving the company more than $50,000 a month by building more accurate models.\r\nCurrently, I work at NBCUniversal, taking up the challenge of building a personalized recommendation experience for each user on NBC\'s app, by recommending the most relevant shows for each user.
Senior Data Engineer
Senior Data Engineer
Jayesh Patel currently works at Rockstar Games as Senior Data Engineer, focusing on developing data-driven decision-making processes on Big Data Platform. He has successfully built machine learning pipelines and architected big data analytics solutions over the past several years. Before joining Rockstar Games, Jayesh held several positions including Senior BI Architect at Kareo, Data Engineer at Alliance Data, BI Developer at North County Transit District and several technical roles at consulting companies. Jayesh earned his BE from Nirma University, India and MBA from San Diego State University where he focused on Information Systems.
The Data Science Expo is for data scientists, business analysts, researchers, educators, students, developers, and tool creators.
Convention Center
Pasadena, CA