Data Science is a wonderful profession and many people, including those in their mid-careers, think of making the big move to the field. But let’s face it: making a move from one career to another is not so easy. There are so many factors to consider, and a lot of patience is required. But at the end of the day, it is doable. Being a lucrative field, data science is attracting a lot of attention from people looking to grow their careers.
But first things first: Who is a data scientist? And, what does the role entail?
A data scientist simply makes the value of data using processes and tools that are machine-learning dependent. The person uses scientific methods and algorithms to gain insights and extract knowledge from structured and unstructured data. For example, a data scientist can use a data analytics and visualization application for extracting useful insights from data.
A data analyst, on the other hand, is involved with translating data from market researches, sales reports, and other sources into a plain language that can be easily comprehended for better decision making. Here are some important things you should put into consideration before making the career shift from a data analyst to a data scientist.
1. Work With the Right People
You will gain more knowledge by working with a highly diverse team, especially where the people around you are more experienced. Therefore, identify and connect with the right pool of talent as you shift career to the data science field.
2. Practice in Your Current Role
It is important to start exercising your skills in your current role even as you contemplate changing career. Importantly, you should not consider yourself too old to be a data scientist. Since the data science field requires impeccable critical thinking and problem-solving skills, with the data available in your organization, you can start practicing in your role as a data analyst today for a role in data science tomorrow.
3. Improve Your Model-Building Skills
Apart from excellent math skills, you will need to improve your model building skills, as well. This will help you to work with other people in solving challenging problems. And, the best way to develop your foundational skills in data science is to work on real-life problems and explore different projects alongside data engineers and other experts.
4. Learn to Position Yourself in the Market
Once you have decided to pursue a career shift to data science, it is important that you differentiate yourself to get hired by the best organization. Therefore, you’ll need to acquire the necessary skills to position yourself well in the industry. In fact, if you can confidently use various data tools and resources for solving the problems at an organization, you can increase your chances of getting hired for your dream job.
With the above tips, you can successfully make a mid-career change to data science.
Before You Make the Shift
Here are four questions to ask yourself when you want to know how to switch to data science job.
What Are My Goals?
Defining your goals will help you to clearly outline your reasons for a career transition. You need to bring into perspective your interest in data science in the short-term and the long-term. This will also help you to determine the suitable time frame within which you can develop the required skills. It is important to keep in mind that high-level goals might demand more focus and extra time to prepare and achieve.
The data science field requires continuous learning, and you will need to fully commit and dedicate sufficient time, especially in the long-term, when you wish to move up your career ladder. Forging the right relationships with mentors in the data science field will be a source of motivation as you start out. They will help you to gain more insights and learn the dos and don’ts as you venture into the field.
What Skill and Education Do I Require?
Do you have the necessary skill set for the data science field? And, by skill set, we don’t necessarily mean your ability to crunch large sets of numbers and data. A data scientist is a critical thinker, innovative, and excellent in problem-solving; using data available to improve an organization. To develop the hard skills in data science such as statistics and machine learning, you should consider enrolling in online classes to gain the technical training.
Here are some skills you require to start a successful career as a data scientist:
- Data science programming languages such as Python or R
- Non-relational and Relational databases such as MongoDB and MySQL
- Data visualisation technologies such as D3
- Machine learning models such as Neural Networks and Regression
- Graph technologies such as GraphX
What is the Cost of Shifting?
As you shift career from data analysis to data science, you may lose your income. Since you are joining the field as a beginner and you need to commit your time to develop and sharpen your skills in data science, you have to find a way of getting trained.
This might force you to forego your paycheck as a data analyst and the salary increments you have gained over the years to a beginner’s salary in the data science field. Prepare yourself well before shifting career so that you can cushion yourself when the ride becomes bumpy before you settle in your new career as a data scientist.
Can I Integrate Data Science into My Current Role?
A strong data background is important for a successful career in the data science field. Any data-driven professional is in a good position to successfully transition to data science. In your current role as a data analyst, you can start using data science even as you look forward to shifting career.
Final Word
The demand for data scientists in organizations has grown over the years, and the potential for career growth as a data scientist is unparalleled. This is because of more organizations acknowledging the importance of analysing data for propelling business growth. With proper preparation, a midlife career change to data science will definitely be worth it.
All the best.
