Midjourney 5.2 a lonely young man works in front of a computer in a dark empty office by Christopher Nolan --ar 3:2

I’ve been in your shoes - the first data science hire at a startup. Despite six years of experience as an applied econometrician, I quickly realized my novice status in the realm of data science. My skills were lacking in areas such as technology, computation, data engineering, and software development. Even my soft skills needed some fine-tuning. In hindsight, accepting the offer might have been a hasty decision.

Are you a junior data scientist about to embark on your first solo gig at a company? Brace yourself for the journey ahead. The company is likely charting unknown territory, trying to unlock data potential without a concrete business case for this venture. If this initiative was truly crucial to their value proposition, they probably would have onboarded a more experienced professional. Regardless, expect to be responsible for running Proof of Concepts, addressing data quality issues, conducting product analysis and managing anything else related to data - including some wild ideas.

But don’t despair - working on real-life projects offers an invaluable opportunity to test your skills under pressure. You’ll learn heaps! However, remember that you won’t have any references or even a co-pilot who might catch glaring errors in your work. You’ll be learning on the job through trial and error - which can sometimes be hard to digest. In my case, I had the fortune of working alongside brilliant software developers and an incredible CTO; so I wasn’t completely alone and gained significant insights about engineering and technology. But yes, I made some colossal mistakes.

The main challenge is that you’ll also shoulder all advanced analytics decisions, processes and workflows related to Data Science projects. This situation sets up a potential failure scenario. Even for an experienced professional, juggling everyday projects while making strategic decisions is no walk in the park. As a result, there’s a high chance you might not meet the company’s needs and expectations.

A time will come when you yearn for companionship in your work and feel the urge to move on. For me, that time arrived when I craved learning from data engineers and other senior data scientists. I bid farewell to my job at the startup and joined a 400 people consultancy firm, which was rapidly expanding its data science team. There, I found what I needed - a dynamic atmosphere teeming with top-notch data engineers, cloud architects, and a diverse group of data scientists.

In conclusion, being the first data scientist in a startup can be a challenging and solitary journey. You’ll need to navigate through uncharted territory, shoulder all data-related decisions, and work under pressure without any guidance or support. However, it’s also an opportunity for growth and learning. You’ll gain hands-on experience with real-life projects and acquire invaluable insights about engineering and technology. But remember that it’s okay to move on when you feel the need to learn from others. Don’t hesitate to join a larger team or company where you can work alongside experienced professionals and continue your learning journey.

So here’s my advice: think twice before accepting a position as a junior member founding a Data Science department. If you’re as daring as I was, then good luck! Feel free to reach out if I can assist you.