Data Science Career Paths, Skills, and Special Projects: Our Best Reads of 2023

2023 may have been the year of the LLM—we highlighted our most popular articles on ChatGPT and related topics last week—but data science and machine learning are far too vast for us to reduce them to a single phenomenon (as inescapable as it might be).

Every day, TDS authors publish excellent work on a staggering range of topics, from the latest tools of the trade to career insights and project walkthroughs. For our final Variable edition of the year, we decided to highlight some of the most memorable and widely read posts we’ve shared around three themes: programming for data scientists, career growth, and and creative projects and opinion pieces. They do a fantastic job showing just how vibrant, diverse, and dynamic this field—and our community—is.

We hope you enjoy our selection, and thank you once again for all your support over the past year.

Programming for Data Scientists

• Coding was Hard Until I Learned These 2 Things
  How do you go from “aspiring developer” to an emplopyed one? Natassha Selvaraj’s viral hit offered actionable advice and a healthy dose of inspiration.
• Pandas 2.0: A Game-Changer for Data Scientists?
  New Python libraries arrive on the scene daily, but Pandas remains a staple for data scientists. Miriam Santos’s helpful overview walked us through the notable features of the library’s major 2.0 release.

• 12 Python Decorators to Take Your Code to the Next Level
  If you’re looking to expand your Python know-how, why not explore the world of decorators? Ahmed Besbes covered 12 of them that you can try out for more efficient code.
• 5 Python Decorators I Use in Almost All My Data Science Projects
  More decorators, anyone? Give your programming toolkit an extra boost by following along Thuwarakesh Murallie’s clear and concise guide.
• 5 Python Tricks That Distinguish Senior Developers From Juniors
  There’s rarely just one way to solve a problem, but that doesn’t mean all strategies are born equal. Tomer Gabay shows how the small tweaks seasoned developers introduce into their code can make an outsized impact.

Career Growth

• 6 Bad Habits Killing Your Productivity in Data Science
  From notebook over-reliance to skipping data versioning, data scientists often find themselves stuck because of unproductive habits. Donato Riccio provides concrete, hands-on advice as a powerful antidote.
• Archetypes of the Data Scientist Role
  Choosing the right path within data science can be tricky given how widely job descriptions vary and how unclear job postings tend to be. To help you along the process, Stephanie Kirmer mapped out the main types of roles you’ll likely end up considering.
• Don’t Start Your Data Science Journey Without These 5 Must-Do Steps
  These are challenging times for job seekers, but there’s no reason to despair. As Khouloud El Alami insists in her well-received post, early-career data scientists have the power to set themselves up for success.
• The Portfolio That Got Me a Data Scientist Job
  Walking us through the nitty-gritty details of creating a compelling data science portfolio, Matt Chapman’s guide resonated with a massive audience of practitioners who aim to stand out amid a competitive field.
• Using OpenAI and Python to Enhance Your Resume: A Step-by-Step Guide
  Why not use new tools to streamline your resume-building process? Piero Paialunga brought together ChatGPT and some Python code to turn an often-tedious task into a much more enjoyable one.
• How to Create an Effective Self-Study Routine to Teach Yourself Data Science Successfully
  If you’ve set yourself some ambitious goals for the coming year, you need a plan that will help you push through challenging moments. Madison Hunter explains, in great detail, how to create a self-study routine that is both effective and sustainable in the long run.
• What I Learned in My First Year as a Director of Data Science
  Everyone wants to advance in their career, of course, but becoming a senior data scientist comes with its own set of challenges. CJ Sullivan unpacked some of the ones she had to overcome in her first year as a director-level executive.

Creative Projects and Opinion Pieces

• How I Built a Lo-fi Music Web Player with AI-Generated Tracks
  Lost in a lot of the hype around AI is its power to inspire some truly innovative projects. Case in point: Aleksandra Ma’s fun (and clever) lo-fi music player.
• Regulating AI: The Case for a Mechanisms-Based Approach
  Efforts to place guardrails around AI development have been equal parts clunky and thorny, with a tangled web of stakeholders vying for influence. Viggy Balagopalakrishnan shared an opinionated take on how this process can become considerably more effective.
• A Pathway Towards Responsible AI-Generated Content
  Within the broader realm of AI, generative tools are responsible for a sizeable share of the social and ethical concerns that remain to be addressed. Lingjuan Lyu’s incisive post charted a roadmap towards a more responsible deployment of this powerful technology.
• Dashboards Are Dead: 3 Years Later
  We focus so much attention on how to produce and present data that its actual use by colleagues in other domains sometimes feels like an afterthought. Taylor Brownlow revisited the concept of dashboards to shed new light on the perennial challenges of collaboration and communication.
• The Forbidden Pages: A Data Analysis of Book Bans in the US
  Data’s power to inform and shape important conversations is on full view in Yennie Jun’s deep dive into the alarming trend of book bans in America, “stories of LGBTQ+ communities and Muslim families and women in science and racism and sexism and even picture books about cows.”
• Free From Limitations: The Validation of Machine Hallucinations at MoMA
  We were thrilled to read Christian Burke’s account of his work on a collaborative human/AI installation at New York’s Museum of Modern Art. As AI gains a foothold in more and more areas of our lives, this is a fascinating look into new directions opening up for creators of all stripes.

Thank you, once again, for supporting the work of our authors throughout 2023! If you’ve enjoyed the articles you read on TDS, consider becoming a Friend of Medium Member: it’s a new membership level that offers your favorite authors bigger rewards for their top-notch writing.

The Variable will be on a short hiatus as we take a break over the holiday season, but we can’t wait to see you again in the new year.

TDS Editors

Data Science Career Paths, Skills, and Special Projects: Our Best Reads of 2023 was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.