Data Scientist Job Roles and Responsibilities

“In God we trust, all others must bring data”– by William Edwards Deming

Data science is a broad field that has touched almost every business domain. From finance to medicine, from IT to manufacturing, data science is everywhere. Therefore, it is no surprise that innumerable candidates are looking forward to streamlining their careers into data science. The biggest question here is how to become a data scientist or how to get a data science job.

Well, in this blog, we will help you map out your career in the data science field. Let’s start from the basics.

What is the Data Scientist Job Role All About?

According to Gartner, a data scientist plays a critical role in a company whose role is to extract useful insights from a pool of data which requires a broad combination of skills. They determine the questions their team should be asking and how they should answer them using the data. They use predictive models for theorising and forecasting. The data scientist job combines elements of both traditions and technical aspects including maths, science, statistician and computer programming.

Sometimes a data scientist is asked to explore data without providing any specific business problem. In such situations, you need to know the business well enough to understand the data and do the analysis.

What does a Data scientist do?

Obviously, a day in the life of a data scientist revolves around data. In simple words, a data scientist gathers data, understands them, and shapes the data in different ways as per the requirements. His work includes:

• Developing and checking new algorithms

• Simplifying data problems

• Coding for data cleaning and data formatting

• Developing predictive models

• Performing data visualisation

• Combining proof of concepts

• Looking for patterns or trends in the raw data

• Pulling, merging, and analysing data

• Meeting, presentations and talking to others are also an important part of a data scientist’s day

Key Roles and Responsibilities of a Data Scientist

A data scientist has to work closely with business managers to comprehend company objectives and design strategies for achieving the goals. He first has to extract the data, sort out essential data, and then use tools to get meaningful insights. SAS, R programming, and Python are the commonly used tools. The exact roles and responsibilities will depend on the company’s needs, industry type and organisation size.

Here are some responsibilities of a data scientist:

• Identify data sources from the collected data

• Analyse huge chunks of structured and unstructured data

• Find solutions and develop strategies for business problems

• Identify trends, and patterns and combine various algorithms and modules

• Use data visualisation techniques and tools to present data

• Assist in the construction of data engineering pipelines

• Extend support to BI developers and other analysts for their projects

• Work with sales and pre-sales team on cost optimisation

• Form analytics solutions for businesses by combining tools and machine learning

• Design, implement and oversee the data pipeline

• Conduct knowledge-sharing sessions with the team

Skills Required to Become a Data Scientist

Every data scientist should have the following skills:

• Knowledge of statistical procedures

• Tableau, Power BI and Matplotlib for data visualisation

• In-depth understanding of data wrangling

• Competitive big data skills

• Statistics software such as SPSS, SAS

• Calculus, probability and knowledge of linear algebra

• Ability to handle commercial issues

• Deep learning and computing

• Strong programming skills including Python, R, SQL, etc.

• Ability to work in a team and multitask

• Updated knowledge of business operations and market trends

• Non-technical skills like communication and problem-solving capability

How to Become a Data Scientist?

You can consider the following steps when aiming to become a data scientist:

1. Get your Bachelor’s Degree: Generally, candidates prefer to pursue a bachelor’s degree in science fields such as engineering, mathematics, IT, or other related fields. This can help build your foundation in the basic concepts and skills as per the data science requirements. Post this, you can take up internship opportunities to hone your skills further.

2. Add Certifications: Getting certifications helps you hone your skills and showcase your dedication to the field. Moreover, it helps to upgrade your skill set as per industry trends.

3. Gain Relevant Experience: Data science is a high-demand field, and getting relevant experience will give you an edge in the cutthroat combination. Be it internships, industry training, freelance work, or an entry-level job in this field, practical exposure is very important.

4. Strengthen your Portfolio: A strong portfolio will get you a high-paying job. Therefore, you should focus on building a strong portfolio with projects or any practical work that displays your skills. This increases your chances of getting picked by the recruiters.

5. Earn a Master’s Degree: It is not mandatory, but if you wish to enhance your skills further you can go for it. Some candidates with different academic backgrounds or opted for a general computer science course in their bachelor’s generally pursue master’s courses with data science specialisation. The most popular choice is an MBA in Data Science programme.

Salary Range for Data Scientist

Data science is among the highest-paid professions in the IT field. The salary range will vary depending on experience, company, city, and your skills. 

• Data scientist salary based on experience: 

• Data scientist salary based on the company: 

• Data Scientist salary based on the city in India: 

Source: Ambition Box

Factors Affecting the Salary of a Data Scientist

Several factors affect the potential salary you can earn as a data scientist. Let’s take a look at a few:

• Experience Level: Your industry experience is a major determinant of salary. Entry-level jobs generally pay less, however, as you move up in seniority.

• Educational Qualifications: Candidates with higher degrees like an MBA in Data Science or a related master’s degree can get a higher salary package. Whereas, someone who has a slightly different educational background might get paid less.

• Skills and Proficiency: Strong skill set and advanced knowledge is also a factor influencing your salary range.

• Location: Every city will have a different cost of living and the demand-supply will also vary which will impact the amount employers pay.

• Company Size: Where a multinational company will pay you INR 14 LPA, a start-up with limited resources might not be able to pay that much.

Oftenly Asked Interview Questions for Data Science Jobs

Your interview will start with some general questions to make you comfortable and learn about your personality and gradually it will turn technical. Here are some of the interview questions examples for data science jobs:

1. Tell me about yourself.

2. Tell me about your hobbies/interests other than data science.

3. What rank would you give yourself for managing workloads?

4. Why did you decide to become a data scientist?

5. Do you have experience working on an extensive programming-based data science project?

6. How do you handle a data set which is missing several variables?

7.  Which metrics have you used to evaluate business performance?

8. Tell me about a few sampling techniques you use.

9. How do you compare two comparable models based on accuracy and performance?

10. What is a p-value? What does it indicate if it’s high or low?

11. What is an imbalanced data? What’s your approach to it?

12. What is your data wrangling and cleaning process before implementing ML algorithms?

13. What is linear and logistics regression? Give examples.

14. How do you create an algorithm?

15. Why do you want to work in this company?

16. What makes you a suitable candidate for this role?

17. Is having a large data amount preferable?

18. What is/are your strengths and weaknesses as a data scientist? How do you plan to overcome it?

19. Have you worked with sensitive information? If yes, did you handle it?

20. Explain the steps of the decision-making tree.

Wrapping Up

Data science is among the most sought-after professions of the current time. As this revolution has just begun, this sector holds immense potential which can be a lucrative opportunity for interested candidates. Once you crack the code on how to become a data scientist, you are on your way to success.

FAQs

Q1. What skills do I need to become a data scientist?

Following are the skills that you must possess as a data scientist:

• Programming

• Probability and statistics

• Data wrangling and database management

• Machine Learning and deep learning

• Data visualisation

• Interpersonal skills

• Cloud computing

Q2. Which course is best for data scientists?

A computer science or MBA in data science course is best to start a career as a data scientist. Apart from this, you can go for an IT course or certificate courses.

Q3. Which job will have high demand in the future?

Job roles such as data scientist, healthcare professional, cyber security analyst, AI and ML engineer, project manager, and digital content creator are in high demand.

Q4. How many subjects are there in data science?

It depends on the type of course you have chosen. The foundational subjects covered in this field of study include statistics, programming, machine learning, artificial intelligence, mathematics, data mining, etc.

Q5. What to do after 12th to become a data scientist?

Start by pursuing an undergraduate degree in fields related to statistics, computer science, programming, or computer applications or a bachelor’s programme with a data science specialisation. You can further go for an MBA in data science to hone your skills and gain expertise in the field.