Shedding light on the scope of labor expectations for junior, mid-level, and senior data scientists
Experience and technical expertise play an enormous role in defining a Junior or a Senior Data Scientist — but what are the business expectations for these levels in the case of scope of labor?
While many resources and job descriptions discuss the technical responsibilities related to each level (or the time spent managing them), there’s a noticeable lack of clarity in the case of the broader business expectations for data scientists at various seniority levels.
In this text, I’ll make clear the scope of labor expectations for Junior, mid-level, and Senior Data Scientists, a framework that has proven invaluable in my managerial role — and may very well be useful for you too if:
- You might be build up a proper Data Science practice and you might be wondering what roles and levels you would like — I consider this might help.
- You might be a Data Science practitioner hoping to advance to the following level (or make the argument to your boss you already are) — this could help too.
So — let’s dive in!
The entry-level Data Scientist is usually for freshly graduate students with a Bachelor or Master’s degree in Data Science/Applied Statistics/Big Data or an experienced Data Analyst who has recently pursued data science certifications.
The Junior/Associate Data Scientist focuses on clear tasks relatively than full projects. Often, the analyses or models are designed by their Manager or a Senior Data Scientist, who also set project timelines and cadence of deliverables.
A Junior/Associate Data Scientist knows the information well and leverages it to deliver analyses or models in response to well-defined tasks.
A Junior/Associate Data Scientist undertakes well-defined data science tasks with some guidance from a manager or senior data scientist.
Junior/Associate Data Scientist expectations:
- Develops predictive models, runs advanced analyses with guidance from manager/senior data scientist.
- Plans work for the upcoming few weeks.
- Translates insights into business recommendations with guidance from manager/senior data scientist.
- Presents findings/technical work to peers and manager.
- Understands and establishes relationships with close cross-functional business areas and direct stakeholders.
- Learns organizational tools, processes and procedures