Professional experience spanning 19+ years in digital transformation, digital strategy, data science, data analytics, education, data mining, machine learning, business analytics, corporate training business intelligence, competitive intelligence, predictive analytics, forecasting, data acquisition, data validation, predictive modeling ,data visualization & project management across domains of strategy consulting, biostatistics, public sector, services , retail, BFSI, & academic domain.

Martin is a data scientist who enjoys using the Python and R programming languages and Command Line Tools to explore, analyze, visualize and present data. Martin believes that anyone, regardless of their background, can learn and benefit from technical skills. In addition to Data Society, Martin has taught Python Programming, Machine Learning, and Data Science courses for Foundation for the Advancement of Education in the Sciences (FAES), Software Carpentry, and General Assembly.
Martin holds an MPH in Epidemiologic and Biostatistical Methods for Public Health and Clinical Research and a certificate in Data Science from Johns Hopkins University, a PhD in Tumor Biology from Georgetown University, an MS in Biotechnology from Jagiellonian University in Poland, and a BA in Biology from St. Mary’s College of Maryland.

Seasoned data scientist with expertise in R statistical programming and scripting, specializing in digital marketing analytics. As a former, corporate marketing executive, Thomas is also experienced in marketing, quantitative analysis and financial modeling, business planning, financial modeling, SEO & SEM marketing, website traffic and customer analytics. As a data scientist, Thomas has worked extensively in machine learning, consulting numerous businesses and organizations on how to leverage algorithms such as linear models, random forest algorithm classification models, Natural Language Processing (NLP) and text analysis, web scraping, data mining of social media, market research, statistical learning, k-nearest-neighbor, k-means, Support Vector Machines, neural networks, and deep learning. Additionally, Thomas enjoys teaching businesses how to make the most of little with other, often over-looked data science skills like geospatial data and heat map visualization, data cleaning, Excel file management, and basic automation with the Google Sheets API.

Abraham has worked with data science for over four years of building models and visualizations for the social development sector. He’s been a professional computer scientist for more than 9 years, passionate about programming and building solutions for clients. Fluent in Python, C#, JavaScript, SQL, Tableau, among others, Abraham is always centered on the goal of making people understand cutting edge technologies that leverage productivity and information insight. On the side, he’s a highly skilled arepa cook, the number one meal for Venezuelans like him.

Founder & Data Scientist at Emdata

Selina is a data scientist, statistics nerd, and R aficionado. She previously used her quantitative and econometric skills for trend analysis on business operations at the Inter-American Development Bank.

Selina holds a M.S. degree in mathematics and statistics from Georgetown University, and M.A. degrees in economics, publish administration, and international relations from Syracuse University. She is a Returned Peace Corps Volunteer, Fulbright Scholar, and Boren Fellow, with professional proficiency in Spanish, Portuguese, and Turkish languages. She is also a guru baker of banana bread and cinnamon rolls.

Gunnar Kleemann holds a PhD in Molecular Genetics from Albert Einstein College of Medicine and a Master’s in Data Science (MIDS) from UC Berkeley. He did post-doctoral research on the genomics of aging at Princeton University, where he focused developing high throughput robotic assays to understand how genetic changes alter lifespan and reproductive biology. Currently he runs Austin Capital Data; an Austin Based Data science consulting company and is an instructor at UC Berkeley’s MIDS (Masters in Data Science) program.

Cyber Security, Strategist with Big-Data and Data Science Expertise. Bobby’s business acumen and strategy with database and user-experience management has significantly improved performance and efficiency within the Department of Defense (DoD), and Comptroller applications. From his B.S. in Finance through his Master’s Degree and Data Science certificate, Bobby is a force of limitless strategic insight for not only business processes/security but into business-oriented program development and design.

Kodie McNamara joined the Georgetown University Mathematics Department in August of 2017, and currently serves as an adjunct professor. He has earned a BA in Mathematics from Gettysburg College (’16) and an MS in Mathematics & Statistics from Georgetown University (’19).

His primary research interests include probability theory and application, numerical methods, mathematical statistics, and mathematical and statistical computing. With his time at Georgetown University, Kodie conducted research concerning the state department of education in Connecticut, alongside other non-profit institutions, in order to appropriately allocate finances. Building mathematical models and providing inferences guided much of his research.

Kodie was a 2016 Teach for America corps member, along with educational experience in the professional setting, leading data science projects in a classroom setting at the Health and Human Services department in Washington, DC. He currently works with Data Society as a consultant and educator, working both with private and government organizations. Many of the computer applications he uses include R, SQL, Python, and MatLab amongst others

Data and analytics professional specializing in collection, management, and use of targeted data for program improvement and strategic decision making. Solving problems for non-profit and government decision makers who rely on complex and disparate data systems is my greatest strength. I am passionate about using data to improve the lives of those who need it the most.

A health informatics educator and researcher with interests in outcomes and cost-effectiveness analytics, patient safety; and decision support tools

Dr. Yaser Keneshloo has a ph.D. in computer science and years of working experience as a data scientist

Dr. Mandi Traud (they / them) received their Ph.D. in Bioinformatics with a Minor in Statistics from North Carolina State University. Dr. Traud teaches many Machine Learning courses for Data Society to professionals at the State Department, Abt Associates, Comcast, and many other organizations. Dr. Traud also has many years of experience working as a data scientist for government projects (statistical analysis, data visualization, network analysis, machine learning) and private sector (machine learning, data visualization, network analysis, statistical analysis, predictive modeling). In their spare time, Dr. Traud also runs a Meetup dedicated to increasing gender diversity in data science.

Rob Mendell is a Microsoft Certified Master Instructor for Microsoft Office. He has enjoyed teaching multiple levels of Excel (and Word, PowerPoint, and Outlook) all over the United States since 1993. He has worked with over 70 law firms and many companies in a wide variety of industries. Rob also provides support and software development in Word and Excel using VBA: templates, automation macros, and customized dialog boxes to speed up the creation of consistent work product.