We recently caught up with Nick Ducoff, VP New Ventures at Northeastern University and Founding Director at Level. We will be chatting about the motivations behind Level and the marketing analytics space. We’ll also be exploring the different program offerings at Level
Hi Nick, Thank you for taking the time to join us for this interview. I’ll kick this off with a few introductory questions
Q : What’s your 1 minute bio / introduction?
A : As VP New Ventures at Northeastern University, I lead a startup team to incubate new business ideas and advance a new model of higher education. Our core team has both startup and academic cred: 80% have startup experience and 80% have a Master’s degree. We developed the Experiential Network which is being scaled by the University to expand on its classic co-op model, and now we’re growing Level, a data analytics bootcamp in Boston, Silicon Valley, Seattle, Charlotte, and online. Previously, I led the content team at Boundless Learning, which provides high quality educational content and resources to replace textbooks. Before Boundless, I co-founded Infochimps, a Big Data platform, and led the company as its initial CEO, raising venture capital and growing the team and business during the company’s formative years. While CEO, I led the acquisitions of Data Marketplace (YC W10) and Keepstream (Capital Factory 2010), and negotiated and closed numerous data partnerships, including with Microsoft, Amazon, and Foursquare. Infochimps was acquired by CSC (NYSE:CSC) in 2013.
After graduating from The University of Texas School of Law with honors, I was a venture capital attorney at a leading international law firm. I’m a Techstars mentor, venture capital LP, and angel investor in Panorama Education and a dozen other venture-backed startups.
Q : Can you tell us a little bit about your background and role at Level?
A : We had been watching the coding bootcamp space develop and identified an opportunity in data analytics. Northeastern offers analytics programs in all of our nine colleges and we saw demand for a noncredit program in an accelerated format. We started with one program in Boston, and expanded to campuses in Silicon Valley, Seattle, and Charlotte. The New Ventures team incubated Level and are partnering with Northeastern’s College of Professional Studies to offer a pathway into the upcoming Master’s of Professional Studies in Analytics.
Q : How did you get into Data Education / Training?
A : I co-founded and led a data startup in the early days of “Big Data” and have been involved in the data community since then. There was a shortage of data talent then and that has magnified as the demand for data analytics skills has risen while the supply hasn’t kept up. We’re seeking to help close that gap with Level.
Q : What is your definition of a Data Scientist / Analyst?
A : Here’s our blog post on that!
Level offers full-time classes for intensive learners, and part-time hybrid classes that accommodate the working professional’s schedule. Because we believe that people should continue learning at any stage of life, Level has a range of data analytics programs to suit different levels of experience
Thanks for that introduction. Now, lets dig into some of the program details
Q : What’s the 1 minute bio / introduction on Level?
A : Level Bootcamp from Northeastern University is a data analytics program where professionals learn data analytics skills hands-on by solving real-world problems and working on capstone projects with industry.
Q : How did the idea for Level come about and what do you hope to achieve with it?
A : Level was created by Top-50 ranked Northeastern University to address the growing role of data in today’s world, and equip professionals across industries with the skills to analyze data and advance themselves. Level offers full-time classes for intensive learners, and part-time hybrid classes that accommodate the working professional’s schedule. Because we believe that people should continue learning at any stage of life, Level has a range of data analytics programs to suit different levels of experience. These include
- Level Set for foundational concepts
- Level for in-depth training on core analytics competencies and tools including SQL, R and Tableau
- Level Focus in Marketing Analytics for today’s demanding, data-driven digital marketing environment
Q : How do you screen and select fellows / students for your program?
A : Level has an online application, followed by a phone screen with our admissions team and a prior learning assessment.
Q : Can you describe the typical background (academic / professional) you look for in your fellows ?
A : There is no typical background for a Level student. We look for intelligent and motivated people from all walks of life who have demonstrated an ability to think analytically. Students come from all sorts of backgrounds, ranging from liberal arts to marketing managers to PhD’s in bioinformatics. That diversity creates cohorts made up of students that each bring something unique to the classroom and creates a robust student experience.
Q : What type of skills or traits do you look for in a prospective fellow?
A : The values we look for above all in a Level student are:
- Ability to think analytically
- Collegiality and fun
We need more programs developed and marketed to the general population to help people become data literate and capable of making data-driven recommendations and decisions. That’s our goal with Level, and is why we’re going up the stack with focused programs (initially in marketing analytics) and down the stack to offer Level Set, the first bootcamp for foundations in analytics.
Thanks for the run down. Now lets talk placement numbers
Q : How many cohorts have you gone through?
A : We have graduated five cohorts, and another five are currently underway (with over 100 students total). We expect to double this fall and are marketing ten cohorts for this September across three programs and four campuses in Boston, Seattle, Charlotte, and Silicon Valley.
Q : Do you run multiple cohorts at the same time?
A : We run cohorts concurrently in Boston, Seattle, Charlotte, and Silicon Valley, and will also be running them concurrently by format (full-time vs hybrid) and program (introductory, intermediate, and focused).
Q : What is your typical cohort size?
A : Cohort sizes range from six to twenty, based on the city and the specific program.
Q : Can you share what your placement numbers look like for your most recent cohort?
A : In a three-month survey of our most recent cohort which graduated in March, only 8% of respondents are still looking for work.
Q : Can you also share your historical placement rate (within three months of graduation of each cohort)?
A : Our first cohort, which graduated in December in Boston, currently has a 100% placement rate based on respondents of a recent six-month survey. Our second cohort, which graduated in March with students in Boston, Charlotte, Seattle, and Silicon Valley, has a 92% placement rate based on respondents of a recent three-month survey.
Q : What percentage of your fellows eventually get Data Scientist vs Data Analyst vs Other technical jobs?
A : Level is designed to help students gain analytical skills that they can apply in a range of roles, including non-technical ones. We’ve seen students transition into technical jobs like “data analyst” and but also into ones that rely on their analytical skillset like “marketing analyst”.
Q : Can you share with us where some of your graduates work or will work?
A : Level graduates are employed in analyst roles at companies like Raytheon, VMWare, IDC, Lending Tree, Neuronix, J. Jill, Salsify, iSoftStone, and Burning Glass Technologies.
Q : Can you share with us what industries your graduates work in?
A : Graduates are working in industries including technology, finance, marketing, human resources, biotechnology, and politics.
Q : How do you prepare your fellows to be very competitive for Data Science / Analyst jobs?
A : Professional development is included throughout the Level curriculum, with resume
and interview workshops and access to an individual career advisor. Northeastern University is ranked #2 best career services by Princeton Review. Students also build a portfolio by working on real-world projects and capstones with industry.
Q : Do you have a hiring day and what percent of students are typically placed from a company they meet at hiring day?
A : N/a
Q : For organizations looking to hire Data Scientists / Analysts what should they look for ; Ivy Degrees, PhDs, MBAs, Extensive experience, Business Acumen, Quantitative Background, Technical chops, grit or determination?
A : Despite the buzz around deep data science, most companies don’t need someone to write machine learning algorithms for them. They need someone who is comfortable with data but can also speak to the rest of the organization. Being an analyst means having the technical skills to uncover insights through working with data and the ability to communicate your findings in such a way that they help the rest of the organization make better and faster decisions.
Professional development is included throughout the Level curriculum, with resume and interview workshops and access to an individual career advisor.
Q : Can you give a short summary of a typical day in the life / week in the life for your fellows?
A : In the full-time Monday-Friday program, the morning is generally a lecture format to
introduce new concepts, and the afternoon is hands-on applications of skills through labs and projects. In the hybrid program, students do coursework online for 10-15 hours per week, and attend a weekly evening class to review the concepts, work on labs and projects, and hear from guest speakers.
Q : How do you improve your process from cohort to cohort at Level?
A : The world of analytics is constantly changing, so as educators, it is our role to ensure we are always changing and improving as well. We collect feedback from students, instructors, and industry partners. multiple times per week. Our Program Manager, who has a Master’s in Education from Harvard Graduate School of Education, is tasked with incorporating that feedback as well as pedagogical best practices, including from our colleagues at Northeastern University.
Q : What skills and tools do you think should be emphasized more in Data Science / Analyst education?
A : Data visualization and the soft skills in presentation– including communication– are just as important as technical skills when it comes to effectively using data in business.
Q : Given the very fast progression in the field, what skills do you think will be most important for Data Scientists / Analysts in the next few years?
A : More important than specific skills or tools will be the prevalence of the analytical mindset across industries and departments. Everyone should be able to analyze data, not just engineers and the most successful players in the field will be the ones who prioritize data literacy and communicating data company-wide.
Q : How does Level differentiate itself from the other offerings out there?
A : Level is the only data analytics bootcamp run by a Tier 1 research university, which enables bootcamp students to leverage the network and brand of a 100+ year old institution with global reach.
Q : How do you help your fellows deal with burnout?
A : We are always accessible to students via online chat or in person, and encourage students to let us know about any issues or stress they are experiencing. We want to make the Level experience a human one, which is why we host activities like social events and weekly student awards.
Q : Are fellows ever asked to leave or are kicked out mid-way through the program or at anytime during the program?
A : Students have left due to personal health and family-related issues though Level boasts a 94% retention and graduation rate.
Everyone should be able to analyze data, not just engineers and the most successful players in the field will be the ones who prioritize data literacy and communicating data company-wide.
Q : Can you give us a sample of the tools, languages and techniques your fellows are exposed to during the program ?
A : In the core Level program, students learn statistical analysis, including tools such as R, SQL, and Tableau, predictive analytics, data modeling, and data visualization. The Level Set program provides a foundation in analytical concepts and frameworks, and our focus in Marketing Analytics includes marketing strategy, customer research, and campaign management.
Q : What do you feel is broken with Data education in general and do you have any suggestions on how it can be improved?
A : Most bootcamps focus on training data scientists, who need to be strong in software development and statistics. There are very few people who are skilled in either of those domains– let alone both.. We need more programs developed and marketed to the general population to help people become data literate and capable of making data-driven recommendations and decisions. That’s our goal with Level, and is why we’re going up the stack with focused programs (initially in marketing analytics) and down the stack to offer Level Set, the first bootcamp for foundations in analytics.
Q : What Data problems keep you up at night?
A : Structuring and joining all of our data so that we can ensure we’re analyzing a complete set. We collect a lot of data from a lot of different places, and that’s typical for many companies. Thus, storing all of the different streams of data and making it queryable across fields and tables is a constant challenge.
Q : Have you faced any major challenges in running Level ?
A : Every day! If it were easy, everyone would be doing it. Part of the fun is solving the challenges that we know about as well as the ones we anticipate. We’re committed to continuous improvement.
Q : What markets / verticals are you currently focused on ?
A : Our program is interdisciplinary and touches on many fields including technology, health, finance, etc. However, we’re also beginning to offer focus programs. Our first focused program is in marketing analytics.
Q : How do you feel the job market differs across different industries / regions in the US?
A : Our focus is in four markets: Boston, Seattle, Silicon Valley Bay Area, and Charlotte. We find Seattle and Silicon Valley Bay Area to be very advanced in analytics capabilities, especially in technology and startups. Boston is also advanced and the analytics activity extends beyond technology and startups into marketing, finance, and healthcare. Charlotte is very strong in finance but still developing analytics capabilities in other areas.
Q : Who are the Data Scientists / Analysts that inspire you?
A : The many named and nameless contributors to open source projects such as R and Hadoopthat have helped put analytics on the map.
Q : Any parting words for Data Scientists / Data Analysts that are just starting their careers?
A : Make your assumptions clear. We’re rarely blessed with all the inputs and thus often need to make assumptions. Insight comes from combining data we’ve got with what else we know or believe to be true. A good data analyst or data scientist will make a recommendation or algorithm marrying the known and the unknown, and a great one will highlight the unknown for the consumer of the recommendation or algorithm.
Thanks again Nick for taking the time to share some of your insights and discuss Level with us. We do appreciate it.
To find out more about Level you can either reach out to Nick Ducoff, engage with Level on twitter @leveleducation or reach out to their former students or Instructors. Level is currently enrolling for their three programs across their four campuses for sessions starting in September 2016.
Also, please stay tuned for the other Data Science Bootcamps Founder Interviews we have in the pipeline at Data Science Bootcamp Founders Interview Series