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Table of contents
1.
Introduction
2.
About IBM
3.
Skills Required
3.1.
Required Technical and Professional Skills 
3.2.
Preferred Technical and Professional Skills
4.
Roles and Responsibilities
5.
Salary
6.
Benefits and Perks
7.
Career Map
8.
Preparation Strategy and Resources
8.1.
Coding Resources
8.2.
Other Resources
9.
Frequently Asked Questions
9.1.
How long does it take to get an offer from IBM?
9.2.
How many rounds are there for experienced candidates in IBM interviews?
9.3.
Do data scientists simply practice statistics?
9.4.
What do data scientists do at IBM?
9.5.
Does IBM offer work from home?
10.
Conclusion
Last Updated: Mar 27, 2024

Data Scientist at IBM

Introduction

Hello Techies!

With the growing realization of the power of data, the demand for skilled professionals who can use raw data to transform, analyze and evaluate has increased. One such job is the Data Scientist. A data scientist's job is to study data to find insights that can be put to use. They are involved in finding the data-analytics issues that present the company with the most opportunity and choosing the appropriate variables and data sets. Everyone that wants to be a data engineer aspires to be a part of top Tech companies, IBM being one of them.

Introduction

Let’s see what the role of a Data Scientist at IBM is like and discuss the strategies to be one. But before that, let’s have a brief introduction to IBM.

About IBM

IBM stands for International Business Machines. It is an American multinational technology company. Charles Ranlett Flint founded the company in 1911. IBM is known for developing and selling software, middleware, and hardware. 

Logo

The company has headquarters in Armonk, New York. The company is best known for cloud computing and data analytics. The company has more than 2,82,100+ employees. Top inventions by IBM include ATMs, magnetic strip cards, hard disks, etc.  

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Skills Required

In this section, we will look at both the required and preferred skills and experience for the role of Data Engineer at IBM.

Skills

Required Technical and Professional Skills 

  • The candidate requires a minimum of 8+ years of relevant experience
  • To be able to use technical architecture for end-to-end analytics, you must have practical knowledge of a variety of cloud-based solutions, including Red Hat, Azure, AWS, and IBM Cloud for data storage and database connections.
  • expertise in analytics and deep data
  • Analysis and forecasting of time series
  • Knowledge of statistical modeling (significance testing, conditional probability)
  • Techniques for linear programming and optimization
  • Modeling and simulation with agents
  • Chatbot Conversational Skills
  • Understanding of Knowledge Graphs, Ontologies, and Agent Development Frameworks (such as SPADE, JADE, etc.).
  • multi-language programming experience with a solid background in a statistical platform like Python, Java, or MATLAB
  • Strong Python 3.5 skills and SQL coding knowledge.
  • leveraging Kubernetes, Docker, and other containerized workloads and services.
  • Processes for integrating data, like Kettle
  • Knowledge of creating AI models (ML, NLP, Neural Networks).
  • Strong business sense is needed to address client problems by comprehending, gathering, and evaluating data to identify emerging trends and make recommendations that would maximize business outcomes.

Preferred Technical and Professional Skills

  • Fluency in English, excellent teamwork abilities for dealing with clients
  • The capacity to manage and make decisions regarding resources and priorities that are in conflict.
  • The ability to delegate as necessary.
  • Must be a capable team leader.
  • The ability to oversee Data Science initiatives involving numerous trainee data analysts
  • Strong communication abilities—oral, written, and interpersonal—for interaction at all organizational levels.
  • The quality to express technological answers and difficult commercial problems clearly.

Roles and Responsibilities

Now, let us see the roles and responsibilities of a Data Scientist at IBM.

Roles and Responsibilities
  • By analyzing data, sharing findings, and participating on product development, a data scientist at IBM may help turn their clients' data into real business value.
     
  • Utilize the most adaptable and scalable deployment choices combined with Best in Class open source and visual tools. You'll strive to find solutions to real-world issues for the sectors that are changing how we live, whether it's looking into patient trends or weather patterns.
     
  • In a client consulting environment, you are responsible for the efficient delivery of data science solutions and services; you should have experience with predictive modeling, optimization, and/or machine learning analytics techniques using tools and programming languages like SPSS, SAS, R, Python, Spark, etc. in a Hadoop-enabled environment.
     
  • Define the most crucial business problems that need to be resolved; develop mathematical solutions; collect data; develop, analyze, and draw conclusions; test; and present to the client. Applying machine learning, data analytics, optimization, and advanced mathematical modeling approaches can improve performance.

Salary

Freshers and employees below two years of experience can make an annual income of 7-8 lakh rupees. Employees with experience between four and ten years may expect an average pay of 10-12 lakh rupees per year as an IBM Data Scientist in India. The average take-home salary ranges between 90-93 thousand rupees per month.

Salary

The tabular representation of the salary of a Data Scientist at IBM is given below.

Range of Salary

  ₹ 10.3  Lakhs to ₹ 12.5 Lakhs per year

Average Annual Salary

₹12,85,974 per year

Monthly Salary 

₹ 90,990 - ₹ 93,384/month

 (The figures presented above are subject to change by IBM)

Benefits and Perks

IBM is a well-known company with a positive workplace culture and good working conditions. The benefits an employee gets entirely depend on the project they are working on or the business unit to which they will be assigned. But apart from those benefits and perks, there are some constant benefits of being at IBM which are -

🩺Health Insurance

 🛣️Leave

 🏢Flexibility at work

🍔Meals

🏖️Team outings

👨‍🏫Soft skill training

📚Job training

💰Reimbursement

💸Financial perks

🎗️Health and wellness

👪Childcare

🧓Retirement plans

🧑🏼‍🤝‍🧑🏽Opportunities to network and connect

Career Map

The role above Data Scientist is Staff Data Scientist. To be a Staff Data Scientist, you must have at least 5+ years of experience in the domain. They assist senior executives in prioritizing/scoping projects, making suggestions, and evangelizing data-driven business choices in support of strategic goals. 

 

Career map

A Staff Data Scientist can be promoted to the post of Senior Staff Data Scientist. They generally have a minimum of 10 years of experience. They act as primary domain experts in the firm. Senior Staff Data Scientists provide mentorship to the junior members.

Preparation Strategy and Resources

As we saw above, the Data Engineer position at IBM has numerous benefits, but it requires a lot of hard work. Along with hard work, smart work is needed as well. The smart work would be to follow effectively designed courses and study plans with complete discipline!

Resources for Preparation

 

Check out the following articles by clicking on the link to access resources that will boost your preparation:

PythonRefer if you are looking for help learning Python, one of the most in-demand programming languages for Data engineers.

Data Warehousing and Data MiningAs mentioned above, knowledge about Data mining and Data Warehousing are some crucial skills that Cisco expects to see in the candidates for the Data Engineer position.

Database Management Systems: To be able to work efficiently with databases, refer to this article to start from scratch and reach an advanced level. DBMS knowledge is one of the most crucial skills a Data Engineer should possess.

AptitudeThis is an essential skill required to clear any interview.

Big DataRefer to this article to learn more about Big Data.

Guide to Kaggle: This is a complete guide to Kaggle for  Data science.

 

Being skilled at problem-solving has become a necessary skill for any tech-related job. We bring you a well-curated list of problems and resources to practice from to master problem-solving abilities:

Test-series: Follow the test series to get a good grip on concepts and test your abilities.

Problems: Master Data Structures and Algorithms by solving the issues.
 

Interview bundle: This link contains the various questions asked during the interview in multiple companies.
 

Contests: Follow this link if you want to practice in a coding contest hosted by the coding ninjas for more practice.
 

Guided paths for coding interviews: This link contains the complete guide on what to do before an interview.

Check out the courses mentioned below to learn more about Machine learning, Data Science, and Data Analytics.

Machine Learning

Data Analytics

Data Science

Coding Resources

Other Resources

 

Also, check out the following link about the roadmap for Data Science.

Frequently Asked Questions

How long does it take to get an offer from IBM?

After applying, you need to wait for at least 2-3week till the process of recruitment starts. Once you clear all your rounds, you will receive a job offer letter from IBM after 10-20days from your final interview.

How many rounds are there for experienced candidates in IBM interviews?

For experienced individuals, the IBM interview process typically consists of two or three rounds. The Technical, Resume Shortlist, and HR phases of the IBM interview process are the most frequent for experienced candidates.

Do data scientists simply practice statistics?

In contrast to statisticians, data scientists are more interested in disciplines like computer science and machine learning. In comparison to statisticians, who are more concerned with the equations and mathematical models they employ for their analysis, they are also involved in developing and using data systems.

What do data scientists do at IBM?

By analyzing data, sharing findings, and participating in product development, a data scientist at IBM may help turn their clients' data into real business value. They utilize the most adaptable and scalable deployment choices combined with best-in-class open-source and visual tools.

Does IBM offer work from home?

Yes, IBM provides work-from-home benefits and a hybrid working mode.

 

Conclusion

In this blog, we discussed the role of a Data Scientist at IBM. We looked had a brief introduction about IBM, the salary and perks that it provides to its Data Scientists, and the job expectations it has in return. We also discussed the essential skills required to grab the position of a Data Scientist in a reputed company like IBM. The blog has resources linked to it to help the candidates prepare well for their interviews and other rounds of becoming a Data Scientist.

Check out IBM Interview Experience to learn about their hiring process.

To know more about the IBM Jobs, the way to get into IBM, or different profiles, you can check out these articles:

You can also consider our online coding courses such as the Data Science Course to give your career an edge over others.

Keep learning and keep growing!

Happy Reading!

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