The field of Data Science is glowing and growing at a high striking speed for the past few years. There was a time when people weren’t much aware of this field, and now working professionals are taking online courses to switch careers in this field. Reason being, High Demand, and High Salary. A report suggests that this field has gained so much popularity that it is even considered the sexiest job of the 21st century.
As of now, there are almost 30,000 job openings available for data science alone in India, and almost 10x (300,000) jobs are available all around the world. The numbers speak for themselves and today we have tons of resources available to opt for a decent data science course (irrespective of stream). From there, Data Science professionals are being picked up by every segment (from small-large) companies in different domains with a handsome package.
Who is Data Scientist?
Data Scientists are experts in working with raw data and accordingly they gather and analyze to generate the desired outcome. Their predictive outcomes help businesses to take effective business decisions and to plan their plan of action for future goals. They use industry knowledge, critical understanding, and predictive assumptions to eliminate the pain point of organizations. The Data Scientists use Python or R Programming Language along with mathematics and statistics to implement the desired outputs.
Moreover, Data Scientists are experts in solving complex issues and exploring what issue needs to get resolved under certain scenarios. Data Science jobs have created a huge surge and become the most trending jobs over the period of time and it is expected to see a hike of such professionals by 11 Million in the next 3 years.
What do Data Scientists do?
Data Scientists are responsible for helping companies to make effective business decisions by working on large data sets. They use mathematics, and statistics, and analyze those data to provide insights in visualization form. They use specific sets of algorithms, tools, and programming languages to perform these actions. The demand for data scientists is high in all segments (small-medium-large) companies.
They are trained to process data through Python’s libraries Numpy, Pandas, Matplotlib, etc., and keep intact effective communications during findings of helpful reports with business owners/stakeholders within the organization. In short, they are core specialized in working with different industries to gather useful information for generating actionable plans for the business.
Skills of a Data Scientist
You can easily segregate skills among technical and non-technical domains. Where the technical domain would require some quantitate skillsets, the non-tech domain would require working on different methods/tools without using any programming languages. However, the skills entail the following topics for a data scientist:
Technical Domain: Programming Language, Database, Mathematics, Data Analysis, Data Visualization, Web Scraping, ML with AI & DL with NLP, Big Data, etc.
Non-Tech Domain: Critical Thinking, Analysis, Effective Communication, Intellectual, etc.
Also, we recommend you check out the following article – Top 7 Skills Required to Become a Data Scientist
Data Scientist Salary
The salary bracket starts between 5-7.5 LPA for Beginners in India. However, the major factor behind this is the level of experience, skillsets, knowledge, critical thinking ability, etc. As you’ll be moving forward in your career, you will be required to ace your career by working with NLP, AI, ML, etc., and to implement them in projects.
Below are the salary data (USA). Let’s have a look at them (experience-wise):
- Data Scientist Level 1 – $85,000–$110,000 (0-3 years of experience)
- Data Scientist Level 2 – $120,000–$140,000 (4-8 years of experience)
- Data Scientist Level 3 – $148,000–$185,000 (9+ years of experience)
- Data Scientist Manager I – $132,000–$164,000 (Team Lead I)
- Data Scientist Manager II – $180,000–$210,000 (Team Lead II)
- Data Scientist Manager III – $210,000–$275,000 (Team Lead III)
Data Scientist Job Roles & Responsibilities
Data Scientist works on predictive models and algorithms to extract those data that can help them to visualize the business outcome. Those data can be fruitful for business stakeholders, clients, etc. and to achieve that data, data scientists are required to use R programming or Python Programming Language. In the past few years, the market has seen a surge in Python developers due to increasing demand in today’s competitive market. The prime reason companies get Data Scientists is to work on data refining, cleansing, collection, and so on. These facts and figures are highly in need for businesses to sustain themselves in the market and based on these patterns, they take appropriate actions.
Besides this, their key job responsibilities are as mentioned below:
- Use of adequate tools to prepare a funnel for segregating structured and unstructured data
- Should be able to use tools for data visualization so that businesses can understand their pain points
- The professional should be able to deliver accurate data to avoid any misjudgment
- Knowledge of programming language, tools & domain for which he/she is applying so that the individual would know where and how to implement which language/tools
- Use of data analysis tools
Types of Data Science Jobs
There are as much as fields available for Data Science today, and they aren’t fixed for the upcoming future. Some may vary, depending on the experience, company domain, etc. Below is the list of Data Science Jobs that exist today:
- Data Scientist: They are responsible for analyzing data that directly helps in taking effective business decisions. Their role combines skills in mathematics, statistics, programming, etc.
- Data Journalist: One of the most trending jobs today, they use statistics to predict the outcome & based on that they issue relevant stories. These methods can be forecasted through data visualization, analytics, mining, etc.
- Data Analyst: They prepare a full-fledged report by analyzing the provided data so that they can eliminate the pain points of the business.
- Data Engineer: Their primary focus is to work on data analysis for building pipelines out of different resources.
- Data Architect: They are the one who defines the tools, technologies, models, and procedures that will be used for collecting, and organizing within the company/organization.
- ML Scientist: They are those professionals who work with machine learning models by working collectively with data and algorithms.
- ML Engineer: Machine Learning Engineers are responsible for working with AI-based modules that help in designing workable algorithms (so that the machine could take input as and when required)
- BI Developer: BI or Business Intelligence Developer is responsible for maintaining business interfaces which include data visualization, future prediction, etc., and helps businesses/organizations to set their future goals.
Best Companies For Data Science with the Average Salary Packages
By now, you must have understood the fact that working in the data science field brings not only a promising career but also a handsome salary as compared to other domains. In this field, only the right skill. experience and knowledge will lead you to land your dream job as a Data Scientist. The jump of Data Scientists jobs has started rising in the past few years and there are certain companies that pay a lot more than an average company could offer.
Below is the list of top data science companies that are offering lucrative packages(Approximate Data) along with the other add-ons:
- Apple – INR 37 LPA (Exp: 2-9 Years)
- IBM – INR 13 LPA (Exp: 2-11 Years)
- Google – INR 34 LPA (Exp: 4-8 Years)
- META – INR 30 LPA (Exp: 2-7 Years)
- Nvidia – INR 29.5 LPA (Exp: 2-10 Years)
- Oracle – INR 16.52 LPA (Exp: 2-10 Years)
- Cisco – INR 17.27 LPA (Exp: 2-10 Years)
- Walmart – INR 29.74 LPA (Exp: 2-7 Years)
- Accenture – INR 12.3 LPA (Exp: 2-8 Years)
- HP – INR 16.9 LPA (Exp: 2-11 Years)
Conclusion
By the end of 2022, we can say that Data Science has become one of the most trending sectors to build a career. Even companies are looking for potential candidates to face and understand the needs of business challenges. The role of a data scientist involves collecting, analyzing, and visualizing all formats of data (structured & unstructured) from various domains (email, internet, social media, etc.) There’s nothing wrong in accepting that the future is going to be more predictive, automotive, and smart than we’re living in today.
