Articles by Jacqueline Nolis
- Prioritizing Data Science Work
As a data scientist, you are constantly deciding what tasks to prioritize. There are many requests from stakeholders but not all have the same impact or innovativeness. Jacqueline recommends prioritizing projects that are both innovative and impactful as they have the greatest potential to change the business. Projects that are not innovative but still provide useful proof can also be valuable. Jacqueline advises against getting stuck doing interesting but irrelevant work or only reporting, as these contribute less to the company. Data scientists should aim to do work that both affects the company and is innovative.