This article discusses three key questions for junior data scientists to consider when thinking about their future careers. The first question is whether they want to be an individual contributor, a manager, or a combination of both. The second question is whether they want to specialize in areas like machine learning, decision science, or analytics translation. The third question is about identifying their passions and what they were made to do. The author emphasizes the importance of continuously revisiting these questions over time.
A Roadmap to Avoiding the “Default Path” and Finding Fulfillment in Work
As a middle manager, it can be challenging to envision your career in the rapidly evolving field of Data Science. However, it’s important to avoid falling into the “default path” and instead make strategic decisions that align with your goals and aspirations. In this article, we will explore three key questions that will help you navigate your career in Data Science.
Question 1: Do you want to be an individual contributor, a manager, or both?
Deciding whether to pursue a managerial role or focus on being an individual contributor is crucial. Many companies emphasize that both paths are equally valuable and offer opportunities for growth. However, there can be pressure associated with this decision. It’s essential to consider where you will thrive and build a solid foundation as an individual contributor before transitioning into a management role. This approach allows you to gain expertise and technical fluency, which will earn the respect of your team and enable you to make informed decisions in the future.
Question 2: Do you want to specialize in Data Science, Machine Learning, Decision Science, or explore other areas?
Data Science is a diverse industry, and it’s important to consider which specialization aligns with your interests and skill set. Roles like Machine Learning Engineer, Decision Scientist, and Analytics Translator have emerged, offering unique opportunities within the broader field of Data Science. However, it’s also valid to explore other areas outside of Data Science, such as Data Journalism, Marketing, Product Management, or entrepreneurship. The key is to continue learning and growing, as this will lead you to the right path.
Question 3: What were you made to do?
Instead of approaching your career as an optimization problem, focus on your unique strengths, interests, and passions. Revisit this question periodically and explore what excites and interests you at the moment. Embrace curiosity and follow your instincts. By pursuing your interests, you may discover new opportunities and open doors that you never thought possible.
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