Acing a data science interview

If you are preparing for an upcoming data science interview or wondering how to prepare for one, this data science interview preparation guide will be of your help.

A data scientist is an expert, who gathers and analyzes structured aa well as unstructured data for organizations. Data scientists are also called data wranglers. They process, and model data, and then interpret it for developing actionable plans.

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Data scientists are also analytical experts as they utilize their skills in technology to find the trends in data. They design data modeling processes, create algorithms and predictive modes for extracting desired data business needs.

There are several different roles available for data scientists. A few of them have been mentioned below:

  1. Data Analyst

Data scientists working in this domain usually have a focus on creating forecasts, identifying strategic opportunities and providing informed and business-related insights, having a major focus on business intelligence. Data Scientists have a major focus on business intelligence. They create dashboards, devise solutions to various business-related challenges, and present data-backed findings to the company stakeholders in an accessible way.

  1. Data Science Generalist                                                                                                                                                        Data science generalist is an important role in the sphere of data science. Data science generalists usually work on:
  • Building simulations
  • Building experimentation systems
  • Making meaningful recommendations
  • Writing optimization algorithms
  • Offering feedback to the company stakeholders based on their findings
  • Running algorithms and models to find actionable insights
  1. Data Engineer

Data Engineers focus on building products or tools used inside and outside an organization. They also build out           data pipelines. Their role significantly overlaps with that of Machine Learning engineers.

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  1. Statistician

The role of the statistician is to deal with both theoretical and applied statistics for achieving required business goals. Statisticians possess the skill of data visualization that can be inferred to acquire expertise in specific data scientist fields.

  1. Machine learning Engineer

Machine learning engineers mainly focus on cutting edge research in areas like NLP, Deep Learning, streaming data analysis, video recommendations, social networks etc. to help organizations develop new algorithmic models that power their streaming and web services.

 Here are a few tips on organizing some key talking points that would showcase a prospect candidate in a positive light during a Data science interview.

  • Mastering Programming Language: For acing a data science interview the candidate must have a keen knowledge of fundamentals like distributed computing and data structure, languages like Python, SQL and R.
  • Algorithmically Implementing Programming Language: After mastering a programming language, one should try to implement the language algorithmically. This will not only help an aspirant to understand how to create and deploy complex machine learning algorithms into work, but also master the language with ease.
  •  Getting Familiar with production deployment environments: Organizations these days are mostly using cloud as an infrastructure model. It won’t be wrong to say that the cloud has been ruling the data science space at present time. Popular cloud vendors like Google Cloud Platform, Azure and Amazon Web Service have made it easier for data scientists to quickly set up a machine learning environment and start working without having to worry about a huge pile of generated data.
  • Getting Hands-on Experience: One of the most crucial parts in the journey of aspiring data scientists is their hands-on experience. It helps them gain practical depth of knowledge to understand the scenario better and help them to demonstrate the skills they already have. Taking up a data science project and trying to build and develop a model provides an in-depth knowledge into the domain one aspires to work on as a data scientist.
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  • Making one’s Digital Presence felt: Data science is growing in almost every social media platform. With everything getting digital these days, one can consider starting one’s own blog or write on social media posts, sharing one’s knowledge as well as showcasing new skills for the community to get noticed. Besides these, a candidate can also try to participate in boot camps, hackathons, contribute to open-source projects or participate in other such competitions to be counted on as an active contributor in the domain.
  • Showcasing know-How About the Industry: The candidates must keep himself/herself updated with the latest news related to data science.  Also, identifying new trends will work as great help in acing a data science interview.
  • Asking relevant Questions: If a candidate wants to be a step ahead from the rest in the selection process, s/he should ask insightful questions during the interview. The reason behind this is, questions help interviewers evaluate the worth of a candidate and how well s/he fits the role. For example, domain specific questions that are completely outside the box could help making the current data science team structure better for the organization. Question about the projects the team is involved in would also be of great help.

 

  • Having knowledge of visualization tools: During the preparation of a data science interview, it is helpful for the candidate to have the knowledge of at least a few basic data visualization tools. For instance, Tableau, Google charts, Qlik are popular tools used by organizations and knowing how to use them will make the interviewer confident that the candidate is suitable for the role.

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Data Science career has been titled as the “Hottest Career of 21st Century” by Harvard Business Review. However, there has been a potential shortage of Data Scientists to meet the technological challenges that are pertaining to the field. In order to fill this gap and to provide high-quality career-oriented education in the domain of Data Science for professionals, graduates as well as undergraduates, HETIC India has recently introduced a 11-month full time advanced program in Data Science.

Powered by complimentary master classes, this short term program is a full-time program offered by HETIC, French School of Digital Leadership

 

 

 

To know more about the program, click on the given link.

 

Admissions are open

You can download the application form with this form



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