Introduction
You’ve always had a knack for solving problems, but now you want to elevate your skills to the next level. You’re curious about how data works and how to make sense of it. You want to understand how businesses can leverage data to improve their operations and make better decisions. And you want to do this while working with other talented people who are as passionate about solving problems as you are!
Do you have an analytical mind?
As a data scientist, you’ll be analyzing large amounts of data to find trends and patterns. You’ll need to be able to think logically and clearly communicate your findings in order to make sense of all the chaos.
You should also have some experience with statistical methods such as linear regression or logistic regression if you want to get into this field.
Do you enjoy solving problems and finding solutions?
Data science is a field that requires problem-solving skills. You need to know how to identify and solve problems, which can be difficult when you’re just getting started.
Here are some examples of problems I have solved:
- How do I get an A in math class? (I got all As.)
- How do I get my first job out of college? (I got three offers!)
- How can I make my parents proud of me? (They were so proud when they found out about my success!)
Can you develop models and test hypotheses?
You’re a data scientist, and you’ve been given the task of creating a model to test your hypothesis. What is your hypothesis?
Let’s say that you want to know whether there is a correlation between the number of hours spent on social media and an increase in depression. Your hypothesis would be: “As people spend more time on social media sites, they will experience increases in depression.”
How do we develop this into a model? We need some numbers so let’s say that we have two groups: one group spends five hours per week on Facebook and Instagram; another spends 15 hours per week. Both groups have their own set of characteristics (age, gender etc).
What does this tell us about our two groups? It tells us that there are differences between them–the first group has fewer members than the second one does; however both groups contain males only since females weren’t allowed access at all times during this study period (which lasted roughly four years).
Are you committed to lifelong learning?
Data scientists should be committed to lifelong learning. This means that you need to keep up with the latest technologies, tools and techniques for your field. The best way to do this is by taking advantage of training courses and books that are available online or in bookstores. Here are some examples:
- Coursera offers free online courses from top universities around the world (including Stanford University). You can also pay for premium access if you want more features such as certificates and grade transcripts/statements.*
- Udemy offers paid video tutorials on a wide range of subjects related to data science, including machine learning and artificial intelligence.*
- Packt Publishing has created an extensive collection of eBooks covering many different aspects of data science including Python programming skills.*
Can you work collaboratively in a team environment?
It’s important to be able to work collaboratively in a team environment. Data science is a collaborative field, so it’s essential that you can communicate effectively with other members of your team. You should also be able to learn from them, which means being open-minded and flexible.
The benefits of working in teams include:
- Sharing knowledge and skills between team members
- Being part of something bigger than yourself
Are you creative, imaginative and resourceful?
Are you creative, imaginative and resourceful?
Data scientists are expected to be able to think of new ways of solving problems. This requires creativity and imagination. Additionally, data scientists often work in teams on large-scale projects that require many different types of resources (software packages, hardware infrastructure etc.). Therefore being resourceful at finding solutions when none seem obvious is an important skill too!
If you can answer “yes” to most of these questions, then I hope you will consider becoming a member of our team!
We are looking for people who can answer “yes” to most of these questions:
- Do you enjoy working in a team?
- Do you like learning new things?
- Are you creative and resourceful?
- Do you have an analytical mind and enjoy problem solving?
If so, then I hope that becoming a member of our team will be an exciting opportunity for you!
Conclusion
I hope this post has given you some insight into what it’s like to be a data scientist at [Company]. If you’re interested in applying for a role with us, please send your CV and cover letter to [email address]. We look forward to hearing from you!
