Beyond the Tech: What Aspiring Data Scientists Really Need to Know

Will AI replace you? Can you overcome garbage data? Why so much emphasis on soft skills?

Photo by Steve Johnson on Unsplash

My latest podcast episode was with Kelly, a fellow data scientist who also has a bit of a nonlinear path. They are also the author of A Friendly Guide to Data Science, a new book for aspiring data scientists of all ages.

We had a really great chat on why a nonlinear career path can be a good thing, what are the limits of generative AI, and what are some practical insights that every aspiring data scientist should hear.

Here are some highlights from our conversation:

Data science isn’t just algorithms

Your coursework probably focuses on heavily machine learning models and speeds through other subjects (my masters program did), but many newbie data scientists are surprised how much real-world data work is trying to handle messy undocumented data. As Kelly puts it: garbage in, garbage out - it’s a popular adage for a reason. Most real data is, unfortunately, very messy and needs a lot of work before it’s usage.

One of the biggest adjustments once you start a real job is just how much time you spend exploring, cleaning, and transforming data. It’s very common to spend days hunting down the right tables, figuring out the correct columns and joins and aggregations for your SQL query, and then spend a fraction of that amount of time on your modeling or analysis.

Nonlinear careers are a strength

Kelly’s path spans NLP, bioinformatics, software engineering, and multiple industries. As you may know, my path spans public relations, marketing, and multiple industries as well. We both agreed that breadth brings perspective, resilience, and unexpected advantages - especially when the job market shifts. We’re qualified for multiple career paths, and our experience pivoting and being resilient means we’d be comfortable doing it again. Plus, every so often, a niche role comes along, and we’re the perfect, unique candidate.

AI is powerful, but overhyped

Generative AI may be in the spotlight, but it can’t replace judgment, context, empathy, or ethical decision-making. Data science remains essential for turning data into decisions, not just text or code.

The truly cutting-edge companies are embracing AI, but putting a boundary on it - they don’t allow it to make decisions for them. That is still the responsibility of humans. Additionally, the true value of AI isn’t replacing tasks that humans have mastered - it’s scaling new tasks we couldn’t scale on human power alone.

Soft skills matter more than you think

Across Kelly’s experience and interviews with other practitioners for their book, communication, collaboration, and respect for stakeholders consistently stand out as career differentiators. Aspiring data scientists mistakenly think they can double down on technical skills and stand out based on those alone, but often it is the candidates with good communication skills and critical thinking that stand out in interviews.

Ethics can’t be an afterthought

Bias, privilege, and human impact are central to data science work. Understanding how technology affects people - and developing empathy for different lived experiences - is a responsibility, not a bonus skill. Unfortunately, it’s one that is often overlooked.

Advice for Aspiring Data Scientists

• Get hands-on early with real data. Kaggle counts - even the Titanic dataset. You have to start somewhere.

• Study job descriptions to guide what you learn. (Companies are literally telling you exactly what they want from candidates.)

• Build domain knowledge alongside technical skills. You’re skills are useless if you don’t know what problems to solve or why they matter.

• Consider adjacent roles. Product or engineering can pivot easily - they have varying levels of technical requirements and require lots of problems solving. Marketing, sales, and finance can allow you to get your hands on data and learn business skills. Even a customer success or product support role at a data-focused tech company can give you good exposure.

• Do something beyond coursework to develop communication and leadership skills. (Again with the soft skills!)