Regardless of whether you’re seeking to enter Data Science at Level 1.0 or you’re wanting to advance to a higher Level. These steps will help you with the next move in your career.
1. Evaluate each of your skills
Step 1 is to compare your skillset with the ones in the Skills Matrix. How solid is your knowledge of statistics? How proficient are you at software engineering? How savvy are you at understanding the way the business functions?
2. Plan out your next promotion
Many businesses hold annual cycles of promotion to advance the position within the company of their employees. According to Julie Zhuo, Facebook’s Vice President of Product Design, the first step in the process of becoming promoted is to make it know that you aspire to level up at your company. At the start of the cycle of progression, state to your manager that you would like to advance in your career. Speak with your manager to inquire about how she ranks the current state of your skillset and find out what is required of you in order to move to the next level.
3. Improve your proficiency with your skills
After you finish analyzing your skillset and discuss your intention to become promoted, it’s time for you to level up your set of skills as necessary.
Are you interested in breaking into a career in AI? Then become rock solid on how statistical models work and study how to implement AI solutions to problems via structured datasets. Do you seek entry into a role as a Data Scientist at Level 3.0? Then make certain that you possess the best math, engineering, and business skills. Equipped with this knowledge, you are well-prepped to negotiate your next promotion when you talk to your manager.
Navigating your way through the levels of the data science career path is exciting. Remember these crucial takeaway points:
- Junior Data Scientists have solid stats skills
- Senior Data Scientists are good at implementing models into production
- Principal Data Scientists understand the way to generate business value
- In order to reach the next level, evaluate how skilled you are, make your intentions to advance known to your boss, and strive to develop excellent skills
Understand that nuances exist at the different levels of data science. Also, different companies may be looking for slightly different emphases on each of the skills. For example, one company might be looking more for solid software engineering skills instead of math skills from Junior Data Scientists. There may be Senior Data Scientists who realize that they have a passion for creating scalable data pipelines and switch into a Data Engineering job. There may be Principal Data Scientists who enjoy developing technical expertise while others are excited in focusing on their business expertise. Regardless of the career path that you choose, improving your skills among these three key areas of Data Science will help you go you far in your career.