How to get placed as Data Scientist?

How to get placed as a Data Scientist? Pretty interesting topic right? Everyone can learn Data Science, Machine Learning, Deep Learning, etc. But they are unable to crack job on Data Science, Why?

We use to get a lot of enrollments for our interview preparation programs from various learners who completed the Data Science Course but they are unable to succeed in their Data Science Interviews.

Let's look into what companies are looking for from Data Scientists.

Data Science Job Requirement -1: Knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.

Data Science Job Requirement -2:

  • Works to design and develop analytical/ data mining/ machine learning models as part of data science solutions.

  • Gather, evaluate and document business requirements, translate to data science solution definition, and ability to implement the solution on a Big Data platform.

  • Ability to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function.

  • Ability to support and guide end-to-end model lifecycle management Create model documentation as per client/ regulatory standards

Interested to look into Data Science Prototype - Click Here

I hope you gonna through above Job Descriptions, Once cross-check whether you have the confidence to work on every point mentioned from above JD's?? Do you have a clear understanding of the Data Scientist lifecycle and his role in the company? Or you are just thinking about Statistics, Python, Machine Learning and Accuracies can help you get a job as Data Scientist?? To speak in interviews, you must have a proven portfolio on Data Science Projects to Showcase in your resume as well as to speak damn confident in interviews.

"Data Scientist's uses statistics, machine learning, deep learning, genetic algorithms, Markov models, python, TensorFlow, AWS, big data ecosystem to build great solutions which drive Return on Investment and better satisfaction than existing process". Building a great solution is the major goal of Data Scientist using various technologies. Focus more on building Solutions or Portfolios on Data Science.

If you are planning to learn a Data Science Program based on the above job requirements enroll for our Data Science Career Transition Program. Our Career Transition Programs contain everything from real-time projects, Data Science Project Prototypes, Documentations, Presentations, etc to everything required to crack a job as a Data Scientist.

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