How to move from Junior Data Scientist
How to move from Junior Data Scientist, you want to avoid making the same mistakes that others did early in their data scientist careers because you want to show your employers that they made the right choice.
As a result, you must figure out how to get up to speed as quickly as possible.
To get started quickly as a junior data scientist, there are three main questions you should ask when joining a new group.
How to move from Junior Data Scientist
You’ve got the job and are now working as a junior data scientist. You should ask three key questions to get your bearings as quickly as possible.
1. Which of the following are the most important Key Performance Indicators in this domain?
2. What are the most important traditional case studies in this domain?
3. Who are the industry thought leaders (internal and external) from whom I should learn?
Consider the first question: What are the most important Key Performance Indicators in this domain?
While you may have participated in Kaggle competitions, and side projects, and worked on your portfolio, you are now part of a large organization’s data scientist team.
That is, you work as a team and within the parameters of what is considered a success within the team and the organization.
This means that the sooner you understand the standards against which your and your team’s work is measured, the better.
This assists you in understanding project prioritization as well as developing your own personal criteria and compass for what you should be working on and what you must be able to demonstrate.
Consider question number two: What are the most relevant classic case studies in this domain?
The industry, the organization, and your team have all faced issues that have been resolved or studied in the past.
People in your group, company and other companies will have a body of working knowledge about what has and hasn’t worked in the past.
Yes, you will be using new techniques, but they will be flavored by what has and hasn’t worked in the past. This means you’ll want to learn about what works, what doesn’t, and what has been tried in the past.
This helps you understand the decisions that managers and senior team members will make, as well as develop your personal approach to data science projects.
Consider question 3: Who are the industry thought leaders (internal and external) from whom I should learn?
There are thought leaders within industries and organizations who drive the agenda, experiments, knowledge, and how to think about what is going on in the small world they inhabit and lead.
Every group and organization will have individuals who they naturally trust and listen to. You must understand who they are, their work, and their points of view, world views, and recommendations.
This will allow you to better understand how your team and organization learn about cutting-edge techniques and applications while also providing you with a natural topic to discuss.
This will also help you keep up with industry news, gossip, firings, and hirings, as well as the softer side of the industry.
You’ve just started as a junior data scientist on a data science team and want to integrate and become effective as soon as possible.
Unfortunately, because you are new to the job and possibly the industry, it is difficult to know what matters.
You should ask three key questions to get your bearings as quickly as possible.
1. What are the most critical Key Performance Indicators for the work of our group?
2. What are the most important traditional case studies in this field?
3. Who are the industry thought leaders (internal and external) from whom I should learn?
The answers to these questions will help you understand how your group and organization learn, who they learn from, what they’ve previously learned and experienced, and how decisions are made.
This will allow you to get up to speed quickly and develop a work style that is ideal for the organization and team you have joined as a junior data scientist.
The next step…
Next, write down your personal thoughts on what these answers mean for your group and organization.
Then, once you’ve compiled this list, find a senior data scientist or group leader and ask them to double-check your answers.
Hopefully, your answers were correct. If not, that’s fantastic – a great learning opportunity as well as a great conversation starter.
