Here's how you can propel your career forward with continuing education in Statistics.

Statistics is evolving subject. New techniques, new algorithms Keep coming. It is important to up to date on new methods through conferences, online workshops, Articles, coursera/linkedin courses etc. You may not need to do any new degree but keep up to speed with latest development can help. Sometimes a smaller course like getting a certification can also help. Also helps to ask lot of questions to your peers and keep discussing new processes to get up to speed With latest developments.

You have to be comfortable with the fact that you will never know everything about the field of Statistics (which sometimes makes me sad). However, you can learn a lot by continuously exposing yourself to information about statistics. The fact that you're reading this article shows that you have an intention to continuously learn. Be sure to join statistical communities (consider volunteering for Statistics Without Borders and similar groups), go to networking events, go to conferences, speak with your peers, watch a YouTube video on Monte Carlo simulations or similar topics, and read some academic works (textbooks, articles, and working papers).

Learning latest about statistics and learning complex algorithms like machine learning, time series analysis , regression models etc can help you make a career move or even grow in your current organization. It can also help in getting industry recognization and increase your presence.

It is good to participate in competitions, attend workshops and certificate programs. It helps to meet more peers / seniors in the same field and know about latest techniques being used and opportunities to know about more job openings and chances of personal growth. Learning from the industry experts also helps in broadening the landscape and try new softwares, statistical techniques which you may not be able to do easily in day to day work.

Specialization becomes a necessity at some point. As I mentioned in another section of this article, you cannot know everything about this field. You eventually should develop expertise in an area that excites you. Some areas that are particularly popular in industry include the following: causal inference, design of experiments, general linear models (GLMs), linear & logistic regression, time series analysis (particularly Garch and ARIMA from what I've seen), and (increasingly) the entire Bayesian Statistical Analysis paradigm. These areas of statistics can be applied to a wide number of fields and industries. Even if none of these areas interest you, there is surely something in the field that you would want to specialize in.