How to Reduce Stress in a Data Analytics Job
There’s a lot of information on how to become a data scientist or a data analyst but there’s little on how stressful these positions can be. As someone first starting out as a data scientist or a data analyst you may unknowingly put yourself into a stressful situation. Today I’d like to share my experiences when I was a data scientist versus a data analyst and my advice to prevent stressful situations from forming.
So much work, so little time
Stress caused by a looming a due date is very common. Reduce stress by working with your stakeholders to prioritize requests and agree on a project timeline and deliverables. Also, double your time estimate to account for any obstacles that may prevent you from making the deadline.
When I was a data scientist, it was time consuming to clean data and train the model to generate accurate results. Stakeholders didn’t understand the model development process and why it took so long. At the start of a project, we had a meeting to discuss timeline and milestones. For example, data preparation 2 weeks, model training 2 weeks, model refinement and validation 2 weeks, summarizing results 1 week for a total of 7 weeks. Listing out milestones helped my stakeholders understand the model development process and helped reduced my stress level because I was focused on completing one milestone at a time instead of the entire project which seemed overwhelming.
As a data analyst, I had multiple stakeholders whose requests were due at the same time. I worked with stakeholders to prioritize requests based on the business impact of working on the request earlier versus later. If your company follows the Agile framework and has sprint planning this makes requests easier to manage. Often there were requests that could be moved to the next sprint and this allowed me to focus on higher business impact requests first and reduced the stress of having to work on all requests at once.
Saying apples and hearing oranges
Data literacy is a problem in many companies and not all stakeholders will understand the analysis results. This often creates stress on both sides as a data scientist or data analyst can be talking about apples while the stakeholders thinks the results are about oranges.
Developing communication skills is key to removing this barrier of understanding. First align results with KPIs your stakeholders understand to close the gap between apples versus oranges.
How to Translate Machine Learning Results Into Business Impact
Explaining model results to executives
Next, use your results aligned to KPIs to tell a story and show how it impacts business performance.
Finally, make sure your presentation is created for the right audience.
How to Create a Successful Data Presentation
Presentation tips for different audiences
By following these three steps I’ve been very successful delivering insights to stakeholders and senior leadership and no longer feel the stress that my results are interpreted as oranges.
You can’t know everything
Every job comes with a learning curve and it takes time to learn all the company tools and become familiar with the data. It’s stressful trying to learn everything and feeling lost when you can’t figure out the answer.
First look at company documentation or search on Google to find answers. I’ve found answers to many questions that way. Next try asking a colleague or your manager. If your question is not company specific but rather how to approach a data analysis or modeling question I suggest looking at Kaggle competitions. Kaggle contests requires you to build machine learning models but the notebooks often contain ways the user explored the training data. I’ve learned a lot reviewing notebooks and entering contests to practice building models and working with different types of data.
If all else fails walk way and come back to your problem the next morning with fresh eyes. I can’t count how many times I’ve done this and figured out a problem in 5 minutes that I struggled with for hours the previous day.
Stay calm and carry on
Everyone feels stress differently and one solution may not work across the board. If you’re feeling stressed in your data analytics role please know you’re not alone but I hope with my tips you’re able to manage and even reduce your stress level going forward.