James is a Senior Data Scientist at Humana where he works on applying Causal Machine Learning to Population Health Problems. Although he is currently working on a Master’s in Biostatistics, he comes to Data Science from a Non-traditional route. He used various online resources to build his quantitative and programming skills. James got his Bachelors in Social work, an MBA as well as an MA in Theology. When he isn’t boring his wife with discussions about causal assumptions and counterfactuals, he is having dance parties/hiking/playing games with his 2 kids.
David has a diverse background spanning many business functions as widely varied as consumer marketing, corporate finance and recruiting. Through all these functions, the value of data has been a unifying feature. David specializes in process optimization and time series forecasting, honed primarily during 5 years at Pandora Media. He is currently the head of Pricing and Business Operations at Honor, a startup in the Senior Homecare industry.
Patrick Butler is a data scientist with background in media, marketing, and advertising. Throughout his career, he was worked within a variety of industries and companies, from small startups to Fortune 100 firms. He holds a B.A. in Psychology from Indiana University and a M.S. in Data Science from the University of Chicago. He is also an alumnus of Data Science Dojo! Outside of his Instructor role at Data Science Dojo, Patrick is an Advisor to an analytics fellowship for post-grads at the University of Chicago and a Data Scientist at Nike. He has a passion for data science education and welcomes the opportunity to support your learning. Feel free to reach Patrick at [email protected]
Eleanor is a Data Analyst with Doximity, the professional medical network for physicians. Her prior experience includes over 6 years as an options trader and quantitative researcher and a B.S. in Mathematics and Philosophy from Harvey Mudd College. She is passionate about helping students of data science take their work to the next level and also committed to leveraging data science and technology to serve nonprofit organizations and other worthy causes.
Silvia Seceleanu is a Data Scientist with over 7 years of industry experience across marketing, finance, fintech and edtech. She graduated with a B.S. in Economics from Duke University and worked for JP Morgan in New York, followed by Square in San Francisco. She now works for Udemy and helps create data products for the marketing and business organization.
Ben is a Seattle based Data Scientist & Engineer working in San Francisco, California. He has extensive experience designing ETL pipelines, databases, websites, and other software products for startups and pre-established corporations.
Sara holds a bachelor’s degree in electrical engineer and a PhD in engineering from the University of São Paulo (Brazil). She worked at IBM and is currently working with Deep Learning solutions for Shell and IBM in the Research Centre for Gas Innovation and the Center for Artificial Intelligence. She has been working as a mentor and instructor of Data Science and Machine Learning courses for over 4 years.
As a data specialist, Bushra currently works in the Health IT sector advising companies on how to use data to address critical business questions. Bushra currently works as a Data Analytics Program Manager at Doximity where she contributes both her leadership and technical skills. In addition to being an expert coder, Bushra is an active member of various organizations, such as the Association for Computer Machinery and #IamRemarkable. Bushra is a humble recipient of the “Tribune Top 20 under 40” Award for career excellence and community service, a testament to her career accomplishments and dedication to diversity, equity, and inclusion initiatives.
Holding a bachelor’s degree in Computer Science, Asim is passionate about responsibly using data to solve high-impact problems. He has worked as a Machine Learning Intern and has spent two years researching Deep Learning Security and Internet Fairness. He is currently an Associate Data Scientist at Data Science Dojo. Beyond technical experience, Asim has been involved in public speaking and debating for eight years and is enthusiastic about imparting the knowledge he has to a broad audience.
In his current role as Vice President of Strategic Initiatives & Operations, Tom utilizes his vast knowledge on deep tech, public-private partnerships, emerging technologies, and digital transformation to successfully manage a high growth portfolio of over $5 billion representing more than 159 companies. Before joining BDC, Tom served as a Program Officer for the Bill & Melinda Gates Foundation, redesigning Senegal’s contraceptive supply chain infrastructure. In addition to his many career accomplishments, Tom was selected as one of Canada’s “Top 40 Under 40” recipients in 2017 for his outstanding leadership.
Usman is a Data Scientist at Data Science Dojo where he works on developing cloud solutions and custom machine learning course content for Data Science Dojo’s enterprise clients.
Usman has bachelor’s degree in electrical engineering. He initially worked as a researcher at a R&D lab, leading and completing several projects in the domains of data analysis, RF systems and software defined networks. He then pivoted to data science and joined Data Science Dojo.
Usman is also a passionate educator and strongly believes that a fundamental understanding of data science is vital for professionals in all domains. He serves as an instructor for multiple modules for Data Science Dojo’s public Data Science Bootcamp as well as on corporate trainings where he focuses on helping businesses understand the value of data-driven decision making for a modern enterprise.
In his spare time Usman enjoys Urdu and English literature, browsing tech videos on YouTube and binging on British crime dramas on Netflix.
Mark is currently a Senior Manager of Portfolio Analytics who holds degrees in Data Science, Agriculture Economics, and Animal Science. He has worked on a variety of big data and machine learning projects across the US and Latin America, including customer churn, part failures, smart cities, and NLP. He’s interested in using AI to improve business processes and lives.
Priyanka Roy is a Data and AI specialist for Banking, Finance, and Healthcare industries at Microsoft. Prior to Microsoft, she served as the Head of Data and AI for Intergen for more than five years.
Taimur Rashid is Chief Business Development Officer at Redis Labs, leading corporate strategy and emerging businesses with a specific focus on AI/ML. Before Redis Labs, Taimur was General Manager and Head of Customer Success at Microsoft, where he helped build one of the largest cloud focused customer success organizations in the industry. Prior to Microsoft, he was responsible global business and market development at Amazon Web Services (AWS) for ~10 years. He helped some of the most innovative companies adopt cloud including Airbnb, CapitalOne, GE, Dropbox, Netflix, Nordstrom, Samsung, and others. Taimur holds a bachelor’s in computer science from the University of Texas at Austin, and currently lives in Bellevue, WA with his wife and three boys, spending his time cross training, hiking, biking, and reading books on business strategy.
Dave has held a variety of technical leadership roles in over 30 years in the software industry. He currently works as a Principal AI Architect at Microsoft, developing trustworthy AI capabilities for the Dynamics business applications. Dave recently completed an MS in Data Science from the University of Wisconsin-La Crosse.
Fahad has over a decade of research, software development, and teaching experience in the area of machine learning, data mining, and distributed systems. He has worked with Bing data mining and social incubation teams on a variety of problems in bot detection, data mining, automatic detection of cause of any abnormal shift in web traffic patterns, user behavior analysis, and multi-dimensional modeling.
I am a Data Science leader, with 10+ years of extensive experience across different facets of businesses; managing data scientists, leading data science initiatives across Product, Growth, Sales, and Marketing. My experience includes defining performance metrics, designing and tracking experiments to drive product success; building machine learning models to detect anomalies, drive account prioritization for effective targeting. Led multiple successful growths and product initiatives by collaborating with Product, Engg, and Marketing teams. Experienced across e-Commerce, Technology, Logistics, and Social media domain, focusing on desktop and mobile platforms. Currently, I am leading Consumer Analytics, Customer Support, and Fraud Analytics teams at DoorDash, Inc based out of San Francisco.
Svetlana is a member of the technical staff at eBay, working as an Machine Learning Engineer in the Structured Data research team. She has also worked on the Search Frontend Applied Research Team at eBay. Prior to working at eBay, Svetlana was a Software Development Engineer at Microsoft. Svetlana holds a Ph.D. in computer science from the University of Cincinnati, and she is skilled in data mining and machine learning.
Jennifer is a Research Fellow in the Department of Biomedical Engineering at the University of Texas, Austin. Jennifer’s bioinformatics and computational work is centered on taking very large, complex data sets and applying data visualization techniques, iterative corrections and machine learning algorithms to derive meaningful interpretation. Jennifer holds a PhD in Tumor Biology from Georgetown University in Washington DC, and possesses 10+ years experience using statistical methods and modeling for cancer research.
Arham is a Solutions Architect, an Instructor, and a passionate information technology generalist. Arham holds a Master’s degree in Technology Management from Texas A and M University. Prior to Data Science Dojo, Arham worked at start-ups in a variety of roles in product planning and application development. He possesses a unique skillset comprising of project management, data analysis, and process improvement.