Data Science is the mysterious word we’ve read hundreds of articles and headlines about, but what is data science? Who are the people who work in data science and what skills do they have? Here is the simplest explanation for you to understand just what data science is according to Jeff Leek and Vasant Dhar: “Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.”

Here are a few necessary skills required to be a data scientist:

Core Skills

  • Strong problem-solving skills with an emphasis on product development.
  • Experience using statistical computer languages, for example, R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques, for instance, clustering, decision tree learning, artificial neural networks, etc.) and their advantages and disadvantages.
  • Above all, Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
  • Excellent written and verbal communication skills for coordinating across teams.
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Soft Skills

  • Curiosity
  • Creativity
  • Communication
  • Critical thinking
  • Business sense
  • Teamwork

Qualifications Required to Become Data Scientists

If you earn a Bachelor’s degree in Computer Science and get certification in BigData/Data Analytics then you can join as a Data Scientist or Engineer intern or employee at a firm

If you earn a Bachelor’s and/or Master’s degree in Applied Mathematics or Statistics and complete online courses in Programming languages and Data Science/analytics then you can apply for jobs in Data science

Similarly, if you earn a Bachelor’s degree in Physics and take online courses in Programming languages and collect professional certifications in Data Science and Machine Learning or get a job as a Data Scientist or Machine Learning Engineer.

Why Choose a Career as a Data Scientist?

Advantages Disadvantages
High in demand It’s a blurry term
Abundance of positions The problem of data privacy
Highly-paid career A large amount of domain knowledge required
Versatile Mastering Data Science is near to impossible
Highly prestigious Arbitrary data may yield unexpected results

Responsibilities for the role of a Data Scientist

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data accuracy

Types of Data Scientist

A Data Scientist gets assigned with different names or designations in different organizations. According to data science central, there are 400 different designations assigned to them. For instance, a marketing company requires a statistician to get in-depth knowledge.

Data Scientist as:

  • Statistician
  • Mathematician
  • Data Engineers
  • Machine Learning Scientists
  • Actuarial Scientist
  • Business Analytic Practitioners
  • Software Programming Analysts
  • Spatial Data Scientist
  • Digital Analytics Consultant
  • Quality Analyst

Tools used by data scientists

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Data Science Tools
JOB ROLE TOOLS
Data Scientist Apache Spark, Apache Pig, Hadoop, Apache Storm, Rapid, Miner, Network X, etc. 
Data Analyst Excel, Pandas, Bokeh, Spotfire, etc.
Data Engineer Hive, Mesos, H Base, Scala, etc. 
Machine Learning Engineer DataRobot, Tensor, Flow, BigML, etc. 

Now that we know a lot about Data scientist, we need to look for a job role which can help us build a career in this field. 

That’s when the role of Vasitum comes into play,  in finding appropriate Data Scientists Jobs

Vasitum is an AI-powered career platform aimed to bridge the gap between the recruiters and the candidates. It is an intelligent solution for the recruitment lifecycle by solving the challenges of recruiters and job seekers while fostering everyone’s ability to reach their full potential.

To find the best role for yourself, all you need is a quick 3-minute registration, and you are all set to start applying for jobs. It is seen that 60% of users on this platform get placed within 30 days! 

Since this career portal is a new initiative, the chances of your application getting noticed at the top are high. It also provides you with a feature of messaging the recruiter, and the best part is everything comes for FREE. Its intelligent system shows you the exact job opportunities that suit you — no beating around the bush, but just meaningful jobs. 

Now, as we know that we can find Data Scientist jobs, so we will now proceed further by looking at some of the tips to get a data scientist job.

  • Master your mathematical and statistical skills
  • Work on various data scientist assignments
  • Deep knowledge of programming languages such as python, R programming, etc. 
  • Presently, there is a wide variety of courses and certifications available both online and offline so as to increase one’s chances of employment with high perks in this particular field. 
  • Organizations these days are ready to hire people who can actually provide valuable inputs that can help in strategizing various policies. One should know how to use their analysis in proving credibility to the company. 

Basic Data Science Interview Questions asked 

  • What is Data Science?
  • List the major differences between supervised and unsupervised learning?
  • So, what are the important skills that are must in python with regard to data analysis?
  • Describe selection bias and its types?
  • Explain exploding gradients?
  • Describe the SVM machine learning algorithm in detail?
  • What are the support vectors in SVM?
  • Can you share an incident where you helped in turning around the project?

Questions You Should Pose to the Interviewer

  • So, will you be able to share with me the ventures I will get the opportunity to work upon if I get hired?
  • I hope you got an opportunity to know more about me and my range of abilities well. By chance, if you have any more inquiries or any doubts about my capabilities, I hope we can examine and address that?
  • Last and most important do not forget to negotiate your salary package and remember not to agree on a small package?

Now that you are through with the Interview and you have been offered a position as a Data Scientist, you should know the art of salary negotiation, especially when you are an aspiring data scientist.

Therefore, Salary negotiation is nothing but a designed series of talks between the employer and the exceptional employee about the package that both the parties agree on.

Points to remember while negotiating salary:

  • Set yourself a baseline, but be determinant.
  • Research the average salary for the position.
  • Never ever quote the salary before the recruiter or the hiring manager.
  • Drain out maximum information from the recruiter before you reveal your expectations.
  • Smile is the basic but most important aspect while making a negotiation so that you don’t look nervous.

Negotiation is an art which also requires skills. However, It cannot be mastered at the first, it needs practice. Don’t make it a number game but focus more on your self-value. You will never be able to get paid what you deserve by avoiding negotiation.

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