Bridging Data Science and Project Management
Many of data science’s biggest challenges are not technical in nature but rather are process-oriented.
That’s why we’ve built Data Science Process Alliance – to help data science leaders, teams, and organizations apply effective project management to improve data science outcomes.
The path to better outcomes is challenging. But it’s also a lot of fun. We hope you join us on this journey!
What our Students are Saying…
“I would recommend the course as it gives you the conceptual frameworks to think constructively on how to better organize data science work within your organization.” “Great to have discussions with someone who thinks from a methodological perspective, but also has hands-on experience with managing data science work. Also, I enjoyed the discussions in the videos between the course instructors.”
Jelle De Jong
“This course was very helpful, in that it refreshed my memory on SCRUM and indeed its limitations and benefits as well as introduced some methods I’d not considered before.”
“I enjoyed it all to be honest. Focusing on real life and workflows was important to me as its great knowing a theory but how do you implement and use is always the killer part.”
“I highly recommend this course. It focuses on essential skills that I immediately put to work on a data science project.”
“I tell my friends and peers – Take this class for the insights it adds to your project toolkit.”
“This course helped me understand how a data science team should think and I came out of the course with a better understanding of how to tackle data science project management problems.”
“I liked that there was offline work that could be done at own free time, combined with live discussions that were very friendly and helpful.”
“Understanding the course content was helpful, but the real value-add we experienced was the 1-on-1 sessions with the DSPA team; it’s how we learned ways to apply the course content to our unique work environment.”
“Implementing the suggestions we got from the DSPA team has helped us set more reasonable expectations for how we should manage projects and helped us develop a roadmap toward doing this better.”
“The course was extremely useful. My only regret is not having taken it sooner. The format was surprisingly easy to follow. Short lectures, followed by interesting discussions amongst the lecturers, made the material very easy to digest.”
“The best part of the course was probably the weekly one-on-one interactions with the lead trainer, which were extremely useful.”
Dr Thibaut Jombart
“As a Scrum Master, the DSPA Team Lead course helped me to look at what I do from different viewpoints. I now not only have a better understanding of how developers look at the Agile process, but also how Data Scientists look at the Agile process.”
“This new understanding will help me to better run my Teams and run different types of Teams. What I liked best, and helped me the most, was the one on one aspect of the course. Our weekly sessions helped me to ask questions that I would not have been able to via e-mail.”
“The course was very useful. It covered both the theoretical and practical aspects of Data Science Project Management. The training also validated my belief that our software development efforts are different than our data science efforts, which means that our data science projects should have a different process than our software development team process.”
“The mentoring sessions were very valuable, as was the ability to go back over the material at any time.”
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.
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 consulting to help like-minded professionals.
I hope you join us on our journey.
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.
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