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New Year's resolutions are a time-honored tradition, a chance for us to reflect on the past year and set goals for the year ahead. The start of a new year can be an especially exciting time, as we look for ways to improve our skills, stay up to date on the latest trends, and make a bigger impact in our work. If you're a data scientist or an analytics professional, there are plenty of ways to set yourself up for success in the coming year! Here are a few New Year's resolutions that are worth implementing in 2023:1. Prioritize Continuous LearningTake some time to identify three new skills you’d like to learn in 2023 and identify at least one online course that will provide you those skills. Continuous learning is incredibly important for data scientists and analytics professionals, as it helps them to stay current in an ever-evolving field. New technologies, techniques, and best practices are constantly being developed and refined. A few places to begin your search would be well-known course suppliers such as Coursera, DataCamp and edX.2. Reconnect With Office Mates There is immense value in the interactions you have with your coworkers, whether preplanned or when you run into organically when you’re in the office. It is important to be intentional about pursuing interactions and conversations, whether they are formal or informal. For employees at organizations with renewed return to office (RTO) policies, plan to be a little less productive on your days onsite so you can strike up those ad hoc conversations. It is important to take advantage of the time you are spending in the office to build stronger relationships with coworkers.3. Refresh Your Resume Although this is a common recommendation, keeping your resume and LinkedIn profile up to do date is always a best practice and something that should be done each new year. With recent headlines announcing layoffs and general economic uncertainty, now is the time to ensure that you are prepared in case you do embark on either a planned or an unplanned job search next year. By regularly reviewing and updating your resume and online profiles, you can ensure that they accurately reflect your current skills, experience, and goals. Be sure to make this a priority in 2023 so that you’re ready to react immediately if the need to market yourself arises!4. Assess Your Working Style There have been many recent headlines announcing organizations rolling out their RTO policies – many scheduled to take effect at the start of 2023. In most cases, return to office generally means being present in the office anywhere from 2 to 4 days per week, but this can vary depending on other factors such as seniority, team dynamics, or personal circumstances. Now is a great time to assess your own working style, so make a New Year’s resolution to do that. Some professionals thrive in a fully remote environment while others crave being back in the office. There isn’t a universal right answer, but you don’t want to work long term somewhere that doesn’t match your style. Resolve to identify where you fall on the spectrum. If you find that your current work environment doesn’t match your style, then begin the process of finding a job that does.5. Create Your Own OpportunitiesDon’t wait for opportunities to come to you – create them! In the fast-paced world of data science and analytics, it is important for professionals to plan ahead and take the time to map out their career goals and to develop strategic plans to achieve them. Make a New Year’s resolution to revisit and clearly define what your career goals are for the next one, three, and five years. It is vital to determine whether your goals include a company change, role change within the same company, or a promotion so you can implement plans and take action towards your goals. It is also important to realize that plans change over time, and with all of the recent disruption it is quite likely that you’ll find that what you laid out even 12 or 18 months ago is now outdated.This post was developed with input from Bill Franks, internationally recognized thought leader, speaker, and author focused on data science & analytics.