From Summer Intern to Full-Time Graduate ML Engineer: My Journey with Sage AI
“This is a story about a boy named Ademola”
When I decided to build my software engineering and data science skills, I set out to work at an organisation where I could learn and grow both. One with the right intersection of growth, best-in-class scientists and engineers, where I could build solutions with significant impact. In the summer of 2023, I found that company; Sage.
A Little Backstory
I’m originally from Nigeria and I moved to the United Kingdom in 2022 to pursue a Master’s Degree in Data Science. My academic background is in Electrical Engineering, but it was data analytics/science that truly sparked my passion during my undergraduate years.
Roche Pharmaceuticals in Lagos is where I had my first break, where I helped pilot a data strategy to help hospitals improve their patient analytics by building a data collection process as well as an insight tool, as well as other impactful projects to help improve the data capability of the organisation. This experience led to me being recruited by the consulting firm PwC, Abidjan, where I played a crucial role in their nascent Data Analytics division. At PwC I worked primarily as a BI Developer, helping businesses make sense of their data and giving data analytics training.
But as the autumn leaves of 2022 started to fall, I moved to the UK to grow my skills as a data scientist.
Diving Into A New Challenge
Having a few years of experience under my belt, a new challenge beckoned. As fate would have it, Sage had just the opportunity: an AI/ML summer internship.
I deeply resonated with Sage’s core values: embracing Humanity, championing Boldness, fostering Trust, and Simplifying complexities. I’ve always held a strong conviction that true, impactful solutions emerge when an organisation places humanity at its core. Moreover, Sage’s commitment to social responsibility through the Sage Foundation further cemented my affinity. It was evident to me that this was a company where purpose and passion converged.
I completed an initial online video interview and a Kaggle challenge. I would successfully apply and get invited to a Hackathon at the Sage Newcastle office alongside ten other applicants.
Three Days That Changed Everything
The hackathon was scheduled for three days; the first day consisted of team-bonding exercises and each candidate meeting with the Sage AI team to pitch why they were the best for the role — the day culminated with some offsite evening activities: 10 pin bowling, pool, and loads of fun.
Day 2 plunged us deep into the hackathon. We were split into three teams, each team with a mentor. Our objective was to develop a prototype for a streamlined Know Your Customer (KYC) process within the Sage ecosystem, aiming to expedite payment processing and approvals while ensuring security and legitimacy. Armed with data, we went to work. My team and I (four members) identified and divided tasks amongst us. One member took on exploratory data analysis while the other two members worked on incorporating external third-party APIs into our overall solution. I was primarily involved in building a machine learning model and deploying the solution.
We had regular check-ins with the mentors, and they were friendly and forthcoming in answering our questions. From that point, it felt like we were already a part of the team, and I knew right then I would thrive in such an environment. We ended the day with a practice run of our presentation to prepare us for the final presentation to the judges.
By Day 3, we had brainstormed and devised a working solution for our idea. When the applause echoed post-presentation, I knew we had nailed it. And indeed, we did. We emerged victorious! It was a relief and a good outcome from the team’s hard work.
A key contributing factor that distinguished our solution from the rest of the teams was we deployed a working solution; however imperfect it was. Because let’s face it, stakeholders value tangible solutions over endless slides.
The Summer of Sage
The joy was indescribable when the offer to intern at Sage AI landed in my inbox. I accepted the offer, and on June 5th, I resumed as an AI/ML Intern at Sage AI. Two brilliant individuals from the hackathon would join me, and we formed the Sage AI Intern team.
We took on the ambitious Cashflow Forecasting project, a time-series challenge, with a clear mission: to equip Sage’s clientele with precise short-term operational insights, empowering them to navigate their businesses with data-driven decisions. Superb mentors, a brilliant tech lead and the entire Sage AI team supported us. I built my software engineering skills as I was primarily tasked with building the service for the project. At the end of the internship, we had our first working version of the project, which we presented to the whole team with great feedback.
During my time in the summer, I was convinced I wanted to work full-time at Sage. The freedom to innovate, with invaluable feedback and an incredible culture and people, made me confident. And so, when the senior leaders asked if I would love to come back full-time, I didn’t hesitate to say yes.
Sailing with Sage AI: My New Adventure
Seven nail-biting days post-internship, the news arrived: I was the newest Graduate ML Engineer in the Sage AI team. Today, I am at an organisation that encourages boldness, celebrates simplicity, and surrounds me with an inspiring culture and exceptional colleagues.
I’m thrilled about the innovative projects on my horizon. Chief among them is the “Make Tax Digital” initiative, a transformative endeavour sparked by the UK’s vision to revolutionise its tax system, ensuring businesses experience a more streamlined and user-friendly tax reporting process.
The future is brimming with possibilities, but one thing’s for sure: joining Sage will always be a decision I look back on with a smile!
