Why You Shouldn't Be A Generalist in Data Science – Career Opportunities

. And it actually was different from what I had expected. I advise that they first consider what sort of data scientist they want to be rather than offering a new library, tool, or resume trick.

This is important since there is no one clearly defined discipline of data science, and employers prefer to recruit highly specialized experts rather than "data scientists" who can handle everything. 

Here are some of the popular data science career positions you can consider while specializing in data science. 

1. Data Engineer

As a data engineer, you'll be in charge of maintaining data pipelines for businesses with a lot of data. This entails ensuring that your data is effectively gathered, cleansed, and preprocessed before being retrieved from its source as needed.

Why is it significant?

It may not be easy to understand why there are individuals whose full-time profession is to create and maintain data pipelines if you have only ever worked with relatively tiny (5 Gb) datasets contained in.csv or.txt files. Here are a few justifications: A 50 Gb dataset won't fit in your computer's RAM, so you usually need to find alternative means to feed it into your model. Additionally, processing that much data might take an absurd amount of time and frequently necessitates redundant storage. It needs specialist technical knowledge to manage that storage.

2. Data Analyst

Your responsibility will be to transform data into useful business insights. You'll frequently act as the connection between the business strategy, sales, marketing and technical teams. Your daily activities will include a significant amount of data visualization. With an IBM-accredited data analytics course in Chennai, you can master the tools and techniques for the data analytics process. 

Why does it matter?

Although highly technical individuals sometimes find it difficult to grasp, data analysts are crucial. So that business strategies can be created around them, someone has to transform a trained and tested model and mountains of user data into an easily understandable format. Data analysts ensure that data science teams save time on tasks that don't provide value to the company.

• Requirements: You'll work with Python, SQL, Tableau, and Excel, among other tools. Besides this, you must be an effective communicator.

3. Data Scientist

You will be responsible for cleaning, exploring, and making forecasts with business value. Model training, model optimization, and model deployment to production will be part of your daily tasks.

Why it matters: You need a method for extracting understandable insights from data that is too large for a person to interpret and too valuable to be ignored. A data scientist's primary responsibility is to translate datasets into understandable findings.

• Requirements; Python, scikit-learn, Pandas, SQL, and potentially Flask, Spark, or TensorFlow/PyTorch are among the technologies you'll be using. While some jobs in data science are completely technical, the majority will also need some business acumen so that you don't solve issues nobody else has.

4. Machine Learning Engineer

Building, improving, and deploying machine learning models into production will be your responsibility. Machine learning models are typically treated as APIs or parts that you plug into a full-stack application or some hardware, but you may also be asked to create your own models.

• Requirements: TensorFlow/PyTorch (or enterprise deep learning frameworks), scikit-learn, Python, Javascript, and SQL or MongoDB are the technologies you'll be working with (typically used for app DBS).

5. Machine learning Researcher 

Your role will be to develop fresh approaches to difficult data science and deep learning issues. Instead of utilizing pre-made solutions, you will be creating your own.

• Requirements: Python, TensorFlow/PyTorch (or corporate deep learning frameworks), and SQL are the technologies you'll be using as part of your ML engineering career. 

Hope you found everything you were looking for. There are tons of opportunities in the data science and AI field but these are the top job roles you can apply for. To secure a lucrative career, join the latest data science course in Chennai and become a certified data science professional as per your domain.