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IBM is Closing the Skills Gap with Data Science Apprenticeships

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(6 min read) The skills gap in the U.S. includes skills and jobs in Data Science. And every company is striving to hire and retain the best talent. Yet, increasing education and job experience requirements do not help employers’ recruitment efforts. To fill this gap, IBM hired the first cohort of Data Science Apprentices in January 2019. 

The IBM Careers Blog team interviewed Serena Bellesi (Ph.D., Senior Data Scientist/Machine Learning Engineer) who manages the Data Science Apprentices team, along with 5 IBM Data Science Apprentices, to learn more about the program and their experiences so far.

 

Tell us a bit about the Data Science Apprenticeship program and the current team of Apprentices?

Serena Bellesi, Senior Data Scientist: The apprenticeship program started as part of the Data Science Elite Team. This gave them a tremendous opportunity to learn about how IBM is helping clients succeed in their journey to AI. Apprentices are now working for the CDO Cloud and Cognitive Software. Their goal is to keep IBM growing and make informed decisions using Machine Learning and AI.

None of the Apprentices have previous tech experience, nor education in data science. Nevertheless, in just a few months, they have all learned sophisticated data science and machine learning on-the-job techniques. They have applied these techniques to client use cases and to IBM internal projects.

At IBM, we truly value the connection between analytical capabilities and a deep understanding of the business. That’s why the Data Science Apprenticeship program is expanding and will span across different business units. While pursuing the next level of expertise in machine learning and AI, our Data Science Apprentices learn all about the goals and challenges characterizing each business and industry.

What is the learning experience like?

Serena: IBM is investing in talent. We provide a unique chance to learn hot skills for a career in tech through digital courses and real use case opportunities. After completing their program, data science apprentices with an understanding of our business will be trained and integrated into the company. They will have also achieved the distinction of Level 1 (Certified Data Scientist) with the Open Group Professional Certification Program for the Data Scientist Profession (Open CDS). In the end, data scientists want to do what they love – get their hands dirty with data, access the best technology available, and keep learning in a company that provides extraordinary benefits and growth opportunities to its employees.

How did you start this journey?

Serena: When I joined IBM as a Senior Data Scientist and Machine Learning Engineer, someone asked me if I was interested in leading this new team and my answer was yes! As a matter of fact, I  wish I had had the same opportunity a few years back. Instead, I had to learn the hard way – after pursuing a Ph.D. and teaching in college, I reached out to potential clients to suggest innovative ideas and solutions. This forced me to reinvent myself and learn everything that school had not taught me.

How did you learn?

Serena: From the web, by trial and error, and with the guidance of more experienced professionals, executives, and entrepreneurs. Working as a consultant is a great learning experience, but besides the financial responsibility and planning, it can be exhausting if you do not surround yourself with passionate and dedicated professionals.

As a manager and a Senior Machine Learning Engineer, leading the Data Science Apprenticeship Program is providing me with the opportunity to help newer generations of data scientists to shape their own future, to mentor them and speed their run to a brilliant and successful career.

What was your background before joining the IBM Apprenticeship program, and what made you interested in the program? 

Darrel Moxam, Data Science Apprentice: Before joining the apprenticeship program, I was mainly focused on completing my associate degree in CST (AAS in Computer Information Systems). I was juggling a full-time retail job and full-time college as a P-TECH high school student.

P-TECH is a high school module that has partnered with IBM and colleges around the world to facilitate students in achieving an associate degree and high school diploma within a four to six-year period. I joined the apprentice program after getting my associate’s degree because I saw an opportunity to join an amazing company. I thought it would be a great way to enhance my skills and develop new ones that could be applied as a Data Scientist. These newly acquired skills eventually paved the path to a great career opportunity.

What it is like to be a Data Science Apprentice? What do you do on a daily basis?

Denise Hernandez, Data Science Apprentice: As a data science apprentice, I get the best of both worlds. I’m learning through online courses, (both internal and external) and I’m learning on the job by contributing to internal projects.

Coming from the first cohort of Data Science apprentices, we have the opportunity to mentor future Data Science apprentices. Currently, I am mentoring a cognitive Software Engineer who is looking to grow her data science skills. By mentoring others I am reinforcing what I’ve learned, and solidifying my understanding of data science topics.

One of my daily tasks involves completing lessons to advance in my online courses. I attend team meetings and broadcasts from the IBM data science community. Here, data scientists showcase their current work and teach new technical skills. We use Python in Jupyter notebooks to perform exploratory data analysis on different data sets. Our apprentice team is using machine learning models and AI to help senior executives make important decisions about our business. We use Watson Studio Local and Cloud, Cognos Analytics, along with other IBM Software.

What education/life experiences prepared you for the apprenticeship?

Jessica Horvath, Data Science Apprentice: My experience working in a neuroscience research lab taught me to think ten steps ahead. In the lab, time management is critical as experiments are both timely and costly. This has translated into the apprenticeship by improving my time management and my ability to juggle online courses, on the job learning and projects simultaneously.

What has been your favorite part of the IBM Apprenticeship program so far?

Jesse Rhodes, Data Science ApprenticeMy favorite part has been the ability to work alongside different mentors and longtime IBMers. Their expertise has been an invaluable source of guidance for me during the program. Watching how they operate day-to-day has provided me with concrete examples of goals that I can work towards.

What’s one piece of advice you’d offer to anyone thinking about joining the IBM Apprenticeship Program?

Samuel Martin, Data Science Apprentice: One of the biggest things you should focus on is learning to multitask and honing discipline. As an apprentice, you will be primarily learning and applying what you learn to projects. On top of that, you may be assigned mentorship activities as well as assigned to shadow senior employees on official business. Being able to juggle all of that while continuously learning will be a big help on your apprenticeship journey.

What is next for the apprenticeship program?

Serena: Next, we are going to have more cohorts of Data Science Apprentices soon. They will all be exposed to different business units and industries and will eventually become Subject Matter Experts in some areas.

What are your top three tips for future apprentices?

I have a few tips for anyone who is interested in joining the Data Science Apprenticeship Program.

  1. Be curious and proactive. Reach out to people to learn what is new in the market and network.
  2. Work on your communication skills. Learn to tell a story and be persuasive.
  3. Learn to work as a team, which implies understanding we all have different skills and can complement and learn from each other.

These are core to a successful career in most fields. After all, anyone can learn technical skills by taking courses or, even better, on the job. Soft skills are the ones that will eventually convince hiring managers to open the door to your next career opportunity.

Learn more about how the IBM New Collar Apprenticeship Program creates new pathways to employment for candidates without an advanced degree.

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