Data Science has risen to become one of the world's topmost emerging multidisciplinary approaches in technology. Recruiters are hunting for people with data science knowledge and skills these days. Entering the field of data science can be extremely rewarding and beneficial to your career due to its tremendous future advancement opportunities.
Data Scientists collect, analyze, and interpret large amounts of data. The Data Scientist job description is a culmination of the work of a mathematician, scientist, statistician, and computer professional. Using advanced analytical tools, a data scientist interprets data and presents it in meaningful information. For more information, check out the best Data Science certification.
As a Data Scientist, my role revolves around collecting, analyzing, and interpreting vast amounts of data. It's a unique blend of being a mathematician, scientist, statistician, and computer professional. Leveraging advanced analytical tools, I interpret data and transform it into meaningful information. To delve deeper, I recommend exploring the best Data Science certification options available.
My responsibilities as a data scientist include:
- Automating the collection process and identifying valuable data.
- Collecting large amounts of raw data, facts, and figures, and converting them into a usable format.
- Applying data-driven techniques to address business-related issues and problems.
- Keeping up with upgrades in analytical techniques.
- Serving as a crucial communication link between the business development and engineering teams.
- Possessing a solid understanding of statistical tests and distributions.
The opportunities in this field are abundant — securing roles as an operation analyst, quantitative analyst, IT systems analyst, healthcare data analyst, data analyst consultant, and more. I believe investing in a Python with Data Science course is a wise career move, promising significant rewards in the future.
Why Choose a Career in Data Science?
It wouldn’t be an exaggeration to say that data rules the industry. Whatever domain or industry you talk about, data has a significant role to play in it. Every organization relies on data analysis to provide better customer service, and that raises the significance of data science and the demand for data scientists. There are multiple reasons why it is a fruitful decision to be a part of this evolving industry. Some of them are:
- There is an ever-increasing demand for data scientists, and if you are proficient enough, you will have countless opportunities. It is fair to say that data science is a secure and long-term career option.
- With rising demand, the salaries of expert and experienced data scientists are unbeatable. You can draw a handsome salary from your employer, and the added perks are definitely a bonus.
- Another reason to choose data science as your career is that there is so much to learn. If you love to learn something new every day, this domain will never let you hit monotony. It is fast evolving, and you will have much to learn and explore.
- Data is king everywhere, so even if you plan to relocate, rest assured that you will find equally good or even better job opportunities at your new location. While the tier-1 cities offer the highest salaries, even the data scientists at tier-2 make a handsome amount.
It is fair to say that choosing data science as your career option is a fruitful decision. Just plan things well and keep learning to be efficient enough to get the best job opportunities.
Top 10 Data Science Jobs for Freshers in 2023
As a fresher, you're probably curious about the various data science career options. Well, you are at the right place. This section will help you know the top 10 Data Scientist jobs for freshers.
1. Machine Learning Engineers
Machine learning engineers are technically skilled programmers whose job is to research, develop, and design self-running software for automating prediction models. As a result, each time the program conducts an operation, it learns from the outcomes in order to perform operations even more accurately in the future. This is one of the highest-paying occupations in today's world.
Roles and Responsibilities
- Design machine learning (ML) systems
- Select the most appropriate data representation methods.
- Research and implement machine learning tools and algorithms.
- Choose data sets.
Average Salary: USD 127,303 / INR 7,31,169 per annum
2. Data Scientists
A data scientist’s role is to collect, analyze, and interpret massive amounts of data. Mathematicians, statisticians, scientists, and computer experts are all included in typical technical roles. Furthermore, this is an excellent career option for those who have an interest in data analysis.
Roles and Responsibilities
- Finding data sources and automating the data collection process
- Discovering patterns and trends by analyzing information
- Performing data pre-processing on both structured and unstructured data
- Creating predictive models and machine-learning algorithms
Average Salary: USD 81,361 (1-3 years) / INR 10,00,000 per annum
3. Business Intelligence Professionals
A Business Intelligence professional’s role is to analyze complex databases to understand current market trends and how they affect company decisions. BI developers must use cloud-based platforms to design, prototype, and manage complex data. To pursue a career in BI development, one must have a strong understanding of data mining, data warehouse design, and SQL.
Roles and Responsibilities
- Write data collection and processing procedures.
- Ensure collecting, storage, and analysis of data is accurate.
- Report data findings to management
- Monitor data collection.
Average Salary: USD 68,500 / INR 1,560,000 per annum
4. Data Analyst
Data analysts’ job is to create and maintain data systems and databases. Apart from this, they fix any coding errors. Statistical tools are used to interpret data by the data analyst. Patterns and trends are given particular attention as they can be beneficial for predictive and diagnostic analytics. Analytical and leadership skills are a must for data analysts. There is a huge opportunity for freshers with an undergraduate or master's degree in computer modeling, analytics, science, or mathematics to get a job in this field. Check out the KnowledgeHut best Data Science certification to advance your career.
Roles and Responsibilities
Here are the responsibilities for the data analytics job for freshers & experienced individuals.
- Use statistical approaches to analyze data and generate reports.
- Create and deploy data collection systems.
- Gather data and maintain data systems.
- Find, analyze, and interpret trends as well as patterns in complex data sets.
Average Salary: USD 69,869 / INR 455,970 per annum
5. Data Warehousing Professionals
Within the framework of a project, data warehousing specialists are responsible for developing data management processes across a company. Furthermore, they construct software applications and computer programs for accomplishing data storage and management.
Roles and Responsibilities
- Develop, design, and create data models.
- Create plans for ETL methods and architectures.
- Verify the results and generate business reports.
- Monitor data loading and queries.
Average Salary: USD 111,347 / INR 5,00,730 per annum
6. Data Architects
The data architect's job is to create blueprints for data management systems. They evaluate a company's potential data sources and devise a strategy to integrate, safeguard, centralize, and maintain them, allowing employees to access vital information at the right time and in the right place.
Roles and Responsibilities
- Provide a framework for accurately replicating a company's big data requirements using data.
- Align a company's IT assets with its business objectives.
Average Salary: USD 121,000 / INR 20,41,159 per annum
7. Business Analysts
Business analysts play a strategic role in identifying problems and suggesting solutions based on the facts found by a data analyst. In the field of data science, this is one of the most in-demand jobs. One must obtain a bachelor's degree in a field such as business administration, finance, or economics.
Roles and Responsibilities
- Create a detailed business analysis that outlines solutions to a company's problems.
- Forecasting and budgeting
- Analysis of variance
- Make a plan and monitor.
Average Salary: USD 74,461 / INR 6,90,000 per annum
8. Database Administrators
Database administrators are responsible for managing, maintaining, and securing data in one or more data systems so that users can do analysis for business purposes. From a technological standpoint, they handle data storage, presentation, data management, and utilization, as well as analysis.
Roles and Responsibilities
- Use database software to find new ways to store, organize, and manage data.
- Debugging; keeping databases up to date
- Assisting with database design and development
Average Salary: USD 97,400 / INR 5,05,780 per annum
9. Game AI Developers
AI Developers work with Gameplay and physics programmers closely. They report to lead designers and work with gameplay designers to develop the game's neural networks and decision trees. They also work along with QA technicians to resolve issues that arise during testing.
Roles and Responsibilities
- Set patterns for the game's rules.
- Create a framework for non-playable characters' artificial emotions and ideas.
- Research and design the AI elements that will enhance the game.
Average Salary: USD 71,295 / INR 2,92,035 per annum
10. Statisticians
Statisticians collect, analyze, and evaluate data in order to find trends and relationships that can be utilized to make business decisions. Regular responsibilities of a statistician include data collecting process design, stakeholder communication, and organizational strategy advising. This job is demanded in both the private as well as public sectors as it combines statistical skills with expertise in other subjects.
Also read - Role of Statistics in Data Science
Roles and Responsibilities
- Gather, analyze, and interpret data.
- Recognize patterns and relationships in data.
- Design data collection process
- Inform stakeholders about the findings.
Average Salary: USD 92,270 / INR 5,50,000 per annum
Top Certifications for Data Science Professionals
Certifications are an excellent way to excel for any professional, irrespective of the domain he works in. It introduces them to the latest advancements in the industry and trains them in the latest tools and techniques that help them in their professional journey. If you are a data scientist, know that you have plenty of certification options which you can opt for to give a boost to your career and level up! Some of the certifications and their respective purposes are listed below.
1. Certified Analytics Professional (CAP)
The CAP certification trains you in transforming complex data units into segregated and significant information. That is the exact ability that an employer looks for in a data scientist. So, when you have completed these certifications, your chances of getting an excellent job opportunity rise.
- Cost: CAP certification costs $495 for the members and $695 for the non-members
- Validity: The certification is only valid for three years.
2. Microsoft Certified: Azure AI Fundamentals
It is a fundamental level certification program for which you do not require prior experience. It is fruitful to opt for Microsoft Certified: Azure AI Fundamentals certification if you have just begun your career in the data science domain. It will brush up your knowledge of machine learning and artificial intelligence. Moreover, you will learn how these principles relate to Microsoft Azure Services.
- Cost: Microsoft Certified: Azure AI Fundamentals certification costs $99.
- Validity: The credentials never expire. You have it for a lifetime.
3. Microsoft Certified: Azure Data Scientist Associate
This certification enables you to utilize machine learning methodologies to implement and execute machine learning workloads on Azure. After completing it, you become well-versed in implementing and managing storage and configuring virtual networks.
- Cost: Microsoft Certified: Azure Data Scientist Associate costs $165.
- Validity: Your credentials never expire. You have it for a lifetime. You do not have to renew it.
4. SAS Certified Data Scientist
It is a combination of SAS-certified advanced analytics professional and SAS-certified AI and Machine Learning Professional certification. It covers data transformation, manipulating data units, and 18 other courses. You need to pass all of them to get certified.
- Cost: SAS Certified Data Scientist certification costs $180 per exam.
- Validity: Credentials do not expire. You get it for a lifetime.
Apart from these listed options, you can find multiple certification programs by different exam bodies curated for data scientists. The fruitful way to choose one is to consider your current professional status, your interest, and ultimate goal in mind. Do a detailed analysis, and it can give a significant boost to your professional journey.
Dive deep into the Promising World of Data Science
Anyone from diverse backgrounds such as engineering, marketing, data science, and IT professionals can apply for these highest-paying job roles in data science. A great way to learn data science online is with the KnowledgeHut Python with Data Science program. There are many opportunities in the data science field. No matter what, technology keeps advancing along with the field. Data analytics is growing fast, and to keep up with the pace, you need to train your skills. Keep tricks and tips handy. These really help along with the complex procedures and processes. Entry-level jobs will be hard but worth it once you get them. If you have prepared yourself and made your potential in power, you have a long way to go! Keep along with the trends and start today.
Wish you all the best for your future!!!
