Reputation is important when it comes to getting ahead in your data science career. The better your reputation, the more likely you are to be promoted. But how do you build a good reputation as a new data scientist? Here are a few tips:

Be a Collaborator

Data science is a team sport. The best data science is often the work of many who collaborated over time. Show that you are not just in it for yourself by being willing to help out your colleagues, even if it's outside of your normal job duties. Collaborating with coworkers will not only build your reputation, but it will also build your knowledge base for the future. When collaborating with others on data science, machine learning, advanced analytics or artificial intelligence tasks remember to always be willing to learn; even if you are not familiar with a task leading with enthusiasm to learn it will enhance your reputation.

Be Punctual + Dependable

No one likes working with someone who is constantly calling in sick or showing up late for meetings. If you're known as someone who can be counted on, people will be more likely to want to work with you. Being punctual and ready to work when you get there will indicate to others that you take your responsibilities seriously.

Be a Solid Problem Solver

When something goes wrong, don't just sit there and complain about it—try to come up with a solution. Be sure to understand the problem clearly and then reach out to resources and see the best possible outcome for the problem. Your boss will be impressed by your initiative, and your colleagues will appreciate not having to deal with the issue themselves.

Conclusion

A good reputation is essential for anyone who wants to get ahead in their data science career. By following these tips, you can start building a positive reputation at work that will help you advance your career.