Data Scientist 2

What You’ll Do

• Every day, you will help solve business problems presented to us by stakeholders using data. You will get a scenario or problem, such as, “We need to reduce cycle times,” and then pull, analyze, and interpret data relevant to that scenario. You will pull data from SQL databases. You will analyze and interpret data using Python, R, or other tools. You will determine patterns or trends and their statistical significance to the problem. To visualize the data, you will use Tableau.

• Once you have done your analysis, paired with a data engineer, you will present your findings to the stakeholder and confirm, refute or simply acknowledge a hypothesis. Your work may be implemented or may develop into something else.

• This role is remote, but you must be able to report to the Costa Mesa, California, office for regular collaboration days.

What You’ll Need

• To thrive in this role, you must have a solid foundation of statistics and data analysis. You must be able to describe a project where you pulled data, analyzed it, identified trends or patterns, determined significance, and delivered insights or recommendations to the business. What was your approach? What tools did you use and why? Did you get to the root cause of the issue? Did you confirm or refute a hypothesis? You must be able to speak to your involvement and decisions at each stage.

• For pulling data, we use SQL so you must be proficient with this tool. To curate and analyze data, we use a variety of languages and programs: Python, R, and even Excel. You can choose whatever tool helps you best, but you must be proficient in either Python or R.

• Excellent communication skills and an attitude of flexibility are a must. Very often, we get into the data and some aspect takes longer than we thought, or we have to pivot and change how we approach a problem. A dashboard works better than a model, perhaps. Then you have to explain to the stakeholder or the team why you made that change or why the deliverable is taking longer than expected. It’s all about being creative in your approach and communicating that frequently and clearly to people who may be less tech or data-savvy than you.