ERIC JENVEY, DATA SCIENTIST, MCGUIREWOODS  Eric Jenvey manages data analytics for McGuireWoods LLP in Richmond. His work encompasses both firm-facing and client-facing analytics, ranging from end-to-end machine learning solutions, to data visualization/reporting. On the client-facing side, he partners with the firm’s attorneys to deliver actionable insights for clients in high-profile litigation and transactional legal matters. He has experience all across the data pipeline -- as a data engineer, data scientist, and business analyst -- in prior roles.

ERIC JENVEY, DATA SCIENTIST, MCGUIREWOODS

Eric Jenvey manages data analytics for McGuireWoods LLP in Richmond. His work encompasses both firm-facing and client-facing analytics, ranging from end-to-end machine learning solutions, to data visualization/reporting. On the client-facing side, he partners with the firm’s attorneys to deliver actionable insights for clients in high-profile litigation and transactional legal matters. He has experience all across the data pipeline -- as a data engineer, data scientist, and business analyst -- in prior roles.

     

  

    
       
      
         
          
             
                  
             
          

          
           
              VISHAL PATEL FOUNDER & CHIEF DATA SCIENTIST, DERIVE  Vishal Patel is a data science consultant and entrepreneur with over fifteen years of experience applying statistical and machine learning techniques in practical applications across a wide range of verticals. He currently runs Derive ( www.derive.io ), which focuses on data science services, consulting, training, and automated advanced analytics products. Vishal also teaches R, Python, and Data Mining as an Adjunct Professor at VCU for their MS in Decision Analytics program. He holds two Master’s degrees: MS in Computer Science (IIT, Chicago), and MS in Decision Sciences (VCU, Richmond).

VISHAL PATEL FOUNDER & CHIEF DATA SCIENTIST, DERIVE

Vishal Patel is a data science consultant and entrepreneur with over fifteen years of experience applying statistical and machine learning techniques in practical applications across a wide range of verticals. He currently runs Derive (www.derive.io), which focuses on data science services, consulting, training, and automated advanced analytics products. Vishal also teaches R, Python, and Data Mining as an Adjunct Professor at VCU for their MS in Decision Analytics program. He holds two Master’s degrees: MS in Computer Science (IIT, Chicago), and MS in Decision Sciences (VCU, Richmond).

     

  

    
       
      
         
          
             
                  
             
          

          
           
              JACKIE GOLDSCHMIDT, DATA ENGINEERING + DATA SCIENCE LEAD, APIVISTA  Jackie Goldschmidt is a data engineering and data science lead at APIVista. Jackie started working with data as a Monroe Scholar and AidData research assistant at William and Mary. Since then Jackie has worked at startups in advertising technology and healthcare. She has experience using data science tools to build visualizations and back end applications, as well as extract insights that drive business value. She's passionate about learning new technology, startups, and the Zen of python.

JACKIE GOLDSCHMIDT, DATA ENGINEERING + DATA SCIENCE LEAD, APIVISTA

Jackie Goldschmidt is a data engineering and data science lead at APIVista. Jackie started working with data as a Monroe Scholar and AidData research assistant at William and Mary. Since then Jackie has worked at startups in advertising technology and healthcare. She has experience using data science tools to build visualizations and back end applications, as well as extract insights that drive business value. She's passionate about learning new technology, startups, and the Zen of python.

     

  

    
       
      
         
          
             
                  
             
          

          
           
              PAUL BROOKS, SUPPLY CHAIN MANAGEMENT AND ANALYTICS PROFESSOR, VIRGINIA COMMONWEALTH UNIVERSITY  Paul Brooks is a professor in Supply Chain Management and Analytics at VCU. He conducts research, teaches courses, and advises students in decision analytics. He uses optimization to develop machine learning algorithms and applies them in various domains. He is co-creator and maintainer of an R package pcaL1.

PAUL BROOKS, SUPPLY CHAIN MANAGEMENT AND ANALYTICS PROFESSOR, VIRGINIA COMMONWEALTH UNIVERSITY

Paul Brooks is a professor in Supply Chain Management and Analytics at VCU. He conducts research, teaches courses, and advises students in decision analytics. He uses optimization to develop machine learning algorithms and applies them in various domains. He is co-creator and maintainer of an R package pcaL1.

     

  

    
       
      
         
          
             
                  
             
          

          
           
              RENEE M. P. TEATE, DATA SCIENTIST, HELIOCAMPUS  Renee M. P. Teate is a Data Scientist at HelioCampus and the creator of the Becoming a Data Scientist Podcast and @becomingdatasci twitter account. She has worked with data for her entire career - designing relational databases, creating reports and analyses, and most recently developing predictive models & dashboards at Higher Ed startup HelioCampus. Renee graduated from James Madison University and the University of Virginia, and lives in Harrisonburg, VA.

RENEE M. P. TEATE, DATA SCIENTIST, HELIOCAMPUS

Renee M. P. Teate is a Data Scientist at HelioCampus and the creator of the Becoming a Data Scientist Podcast and @becomingdatasci twitter account. She has worked with data for her entire career - designing relational databases, creating reports and analyses, and most recently developing predictive models & dashboards at Higher Ed startup HelioCampus. Renee graduated from James Madison University and the University of Virginia, and lives in Harrisonburg, VA.

     

  

    
       
      
         
          
             
                  
             
          

          
           
              Miriam Friedel, Ph.D., Director of Data Science, Metis Machine/Skafos.ai  Dr. Miriam Friedel has spent over fifteen years in scientific and technical fields spanning theoretical physics, software engineering, transportation, neuroscience, and machine learning. She currently leads the data science team at Metis Machine, a start up in Charlottesville, VA. Metis Machine built Skafos.ai, the ML platform for iOS developers, offering push-button deployment to the edge. Prior to her current role, Miriam was a Director and Senior Scientist at Elder Research, where she lead the commercial business unit and helped clients in a range of industries achieve ROI from machine learning. Her unique background helps her bridge the gap from technical details to strategic insights, increasing collaboration across disparate functional teams.  Miriam received her ScB in physics from Brown University and her PhD in Physics from the University of California, Santa Barbara. She is a co-author on over fifteen peer reviewed articles, and outside of work, spends as much time as possible practicing yoga and being with her two daughters.

MIRIAM FRIEDEL, PH.D., DIRECTOR OF DATA SCIENCE, METIS MACHINE/SKAFOS.AI

Dr. Miriam Friedel has spent over fifteen years in scientific and technical fields spanning theoretical physics, software engineering, transportation, neuroscience, and machine learning. She currently leads the data science team at Metis Machine, a start up in Charlottesville, VA. Metis Machine built Skafos.ai, the ML platform for iOS developers, offering push-button deployment to the edge.

     

  

    
       
      
         
          
             
                  
             
          

          
           
               ELIZABETH HAUBERT, SEARCH RELEVANCE CONSULTANT, OPENSOURCE CONNECTIONS   As a relevancy engineer and data architect, Elizabeth can engineer a solution to your data goals. With twelve years experience in high-performance systems, she has worked with a spectrum of data transformation needs from high-rate, high-precision time-series sensor data to terabyte-scale text and image retrieval systems for the US Patent and Trademark Office.  At a semantic level, she has worked at person identification and classification systems both in public and private-facing systems. Her work with Duke Health system helped patients better locate doctors by name, location and treatment programs. She has worked with Retail Relay to prototype internal-facing customer identification for retail fraud prevention.  When you ask Google  What is learning to rank? , Liz has the first blog post to come up!  Liz’s Master thesis was in early work with image-based recommender systems.

ELIZABETH HAUBERT, SEARCH RELEVANCE CONSULTANT, OPENSOURCE CONNECTIONS

Search relevance is all about marrying the nuts and bolts of data engineering with the art of constructing a user experience. In recent years, Elizabeth has worked with a spectrum of data transformation needs from high-rate, high-precision time-series sensor data to terabyte-scale text and image retrieval systems. Her current passion is setting up the analytics, infrastructure, and processes needed to bring machine learning to the tasks of search relevance.