How to become a Data Scientist? My journey, overview of skill set, practice tips

Data science can be rewarding beyond a big paycheck. Large firms pay well, but smaller ones may not. If you love research and discovery, it is worth it.
Miss Joshua Miller · 5 days ago · 2 minutes read


Data Science: A Journey of Curiosity and Communication

My Journey to Becoming a Data Scientist

My path to becoming a data scientist wasn't straightforward. Initially pursuing electrical engineering, my journey took an unexpected turn when I discovered my passion for programming. Through hands-on projects and competitions, I honed my skills and immersed myself in the world of research.

Skills You Need to Become a Data Scientist

Hard Skills
  • Programming: It's a tool, not a necessity. No-code platforms and AI assistants can make programming less critical.
  • Algorithms and Mathematics: Essential for understanding and applying machine learning algorithms.
  • Domain Knowledge: Vital for framing problems and creating effective solutions. Understanding the business landscape is key.
Soft Skills
  • Communication: Convey your findings in terms of business outcomes, focusing on how data can impact revenue or cost savings.
  • Curiosity: Uncover opportunities for improvement by asking why and exploring new avenues.
  • Adaptability: Embrace change and stay flexible amidst evolving data formats and processes.

How to Start Your Journey as a Data Scientist

  • Learn Machine Learning Algorithms: Understand the basics, explore different tasks, and determine when to train your own models or use pre-trained ones.
  • Learn Programming or No-Code Tools: Choose a language (Python or R) or leverage no-code tools to instruct computers how to extract value from data.
  • SQL Proficiency: Master the standard language for interacting with databases and extracting data efficiently.
  • Learn by Doing: Hands-on projects and Kaggle competitions are excellent platforms to apply your skills and gain practical experience.
  • Improve Communication Skills: Blog about your projects, explain concepts to family, and engage in conversations to enhance your ability to convey complex ideas.

Conclusion: Embrace the Journey

Becoming a data scientist is a continuous adventure, not a linear path. Embrace learning, stay adaptable, and never cease to ask questions. The most fulfilling part lies not just in the paycheck but in the joy of discovery, the power of insights, and the immense satisfaction of turning raw data into actionable knowledge. Just like a well-written code that reads like prose, let your data science journey be an elegant tapestry of curiosity, understanding, and impact.