Bridging the Worlds of Data Science and Project Management
It is ironic that data science, a field built upon rigorous scientific methodologies, has yet to adopt much rigor from project management approaches. The website’s mission to help change that.
While most project management guides are framed from the lenses of other industries like software engineering, this site reviews leading project management approaches and evaluates them from a data science perspective.
Armed with an appreciation of the need for project management, a broad understanding of project management approaches, lessons from other companies, and motivation to continue exploring data science project management, you will more effectively convert data science investments into sustainable value.
Dr. Jeffrey Saltz, MBA
Data Science Professor, Syracuse University
I’m a professor at the iSchool@Syracuse University, where I lead the applied data science program and do research on how teams can best execute data science projects. My previous 20+ years of industry experience has often focused on building new teams that leverage emerging technologies and data analytics to deliver innovative business solutions.
In my last corporate role, I worked at JPMorgan Chase. At JPMC, I reported to the firm’s Chief Information officer while helping to drive innovation throughout the firm. I also held several other key management positions at the company, including CTO (Consumer and Community Banking Risk Management), Chief Information Architect (Chase Financial Services), global head of eBusiness technology and vice president of computational technology. I previously served as chief technology officer and principal investor at Goldman Sachs/Goldman Sachs Ventures, where I invested and helped incubate technology start-ups. I started my career as a programmer, project leader and consulting engineer with Digital Equipment Corp (now part of HP).
I received my B.S. in computer science from Cornell University, an M.B.A. from The Wharton School at the University of Pennsylvania and a Ph.D. in Information Systems from the New Jersey Institute of Technology.
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Nicholas J Hotz, MBA, PMP
Data Science Program Manager, Dish Network
Having lived in four continents and traveled to over fifty countries, I am fortunate to have learned from a diverse set of teachers ranging from multinational CEOs to malnourished kids living on some of Earth’s most remote corners. One key lesson I’ve learned: regardless of the situation, usually most of the pieces exist to substantially improve conditions, yet they are often not put together. One key element to put the puzzle pieces together is the ability to effectively collect data, convert data into information, and drive strategies from information.
Still in its infancy, data science’s promise to transform industries and societies often lags behind its capability. I believe this is largely due to the lack of appropriate project management practices applied to data science environments. I aspire to accelerate these transformations by applying the knowledge I’ve gained to my professional career, academic research, and this website.
I hold an M.B.A from Butler University, an M.S. in Data Science from Indiana University, and three certifications: Certified Scrum Master, Certified Scrum Product Owner, and Project Management Professional. Currently, I bridge the worlds of project management and data science as the Product Manager for Enterprise Data Science at Dish Network in Denver.
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Training and Consulting
Data scientists, project managers, students, government agencies, and corporations have reached out to us for training or consulting services. To support their needs, Jeff and I have helped launch the Data Science Process Alliance which offers:
- Data Science Practitioner Certification: an introductory short course on how to be an effective data science team member
- Data Science Team Lead Certification: an in-depth course for those aspiring to manage data science projects and lead teams
- Enterprise Consulting Services: guidance to help organizations design, build, and manage effective data science functions
- Data Science Process Alliance Community: a membership portal for connecting with and learning from like-minded members