Career stories: The math-music connection in data science

When Javier signed up for a programming course during the pandemic, he had no idea that his career was about to shift from the world of music to data science. As his interest in AI and computer science grew, Javier found a community at LinkedIn that supported his growth and provided more opportunities to learn and lead than he could have imagined.

Making the leap from music to LinkedIn Engineering with REACH

My journey to LinkedIn and passion for coding came from an entirely different background than programming. After studying math and music in college, I performed as a professional violinist touring around the world and composing music for television and film for 15 years. 

During the pandemic, I discovered data science after my friends suggested I take programming courses. I became super interested in machine learning and wanted to make a shift in my career, so I was excited to discover LinkedIn’s apprenticeship program for people with non-traditional tech backgrounds like me: REACH. While I was an apprentice, I was given the opportunity to learn and develop skills and also got to have a hand in LinkedIn projects. 

I am fortunate that I found a second passion in life. My team and mentors were welcoming and flexible with me as I leaned into my role and adapted to how we work at LinkedIn. It’s been a smooth transition since I also worked remotely during my music career. There’s a great culture of work-life balance at LinkedIn. I can adapt my working hours to California or Chicago hours to accommodate my team’s workload, and the flexibility adds to the balance. Although I love working remotely, I think it’s equally important to further connections with your team in person. I visit the Mountain View office each quarter to share coffee, lunch, and thoughts about our projects at LinkedIn with my team members.

Refining the LinkedIn member experience

In my role at LinkedIn, I’m on one of the consumer-facing teams responsible for the algorithm recommending the feed to LinkedIn members. I program in Python, Scala, and Java as I toggle between analyzing data, running machine learning experiments, and evaluating business impact.

In my first big project, I experimented with sampling our training data for the algorithms. It was thrilling to work with data on a different scale than what I was used to in my personal projects; I went from working with tables of 10,000 rows to 500 million! Using big data technologies like Spark and Hadoop, I sampled different data to feed our algorithms, which turned into business metric gains that I also learned to interpret. I still remember the anticipation right before I pressed the button to share the benefits of my model with 10% of LinkedIn members.

I also love keeping tabs on the member experience through on-call shifts, which is when I’m responsible for LinkedIn’s feed worldwide. If something goes down on a data generation pipeline that will affect our members, I can immediately jump in to solve the issue. The decisions I make in those couple of minutes to ensure that I can effectively direct traffic so as to not impact the experience of millions of members makes the work even more rewarding.  

Exploring engineering passions

We have a collaborative culture at LinkedIn, which is one of my favorite things about working here. I consult with other teams and ensure that my work positively impacts them by sharing our data and technologies for their own algorithms. I’m also in touch with my REACH cohort members, and I founded a data club for data science and machine learning apprentices who are just starting at LinkedIn, just like I once was. It’s been fantastic to meet with current and former apprentices and learn from organizations across LinkedIn as we share our experiences.

My advice for engineers in the REACH program or looking to get into the industry is to find where your passion is—mine happened to be machine learning and using those tools to solve problems. My team uses machine learning to create a meaningful experience whenever our members join the LinkedIn feed. I think it’s essential to develop a passion for the business and social purpose of what we do here. This is a job with a mission: technologies come and go, but we must be curious about how we can make things better. That instinct of curiosity will spread through the next thirty years of technologies that we develop. 

About Javier

Javier holds a Master’s in Music from the University of Michigan and a Bachelor’s in Mathematics and Music from the College of Charleston. Before joining LinkedIn, he composed and performed as a professional violinist for 15 years. His current role is as a machine learning engineer on LinkedIn’s Feed AI team. Javier enjoys watching and playing soccer with his son and composing music in his home studio in his free time. 

Editor’s note: Considering an engineering/tech career at LinkedIn? In this Career Stories series, you’ll hear first-hand from our engineers and technologists about real life at LinkedIn — including our meaningful work, collaborative culture, and transformational growth. For more on tech careers at LinkedIn, visit: lnkd.in/EngCareers.