Data Science Career Trend in 2021 for Entry and Mid-Level Professionals

Data Science Career Trend in 2021 for Entry and Mid-Level Professionals

Data science Career and analytics is currently one of the top rated careers in recent times and is projected to double in demand in the year 2021. According to global statistics, it has generated revenue of $5 billion and is expected to grow to $19.4 billion in the coming year. Eighty- four percent of multinationals have launched great initiative in this discipline to accelerate decision making and improve business efficiency and accuracy. More companies now demand data professionals including sectors such as education, health, finance, marketing, engineering, and many more.

A report recently published by McKinsey report has shown that “The United States alone is running out of supply of big data specialist to the tune of 140,000 to 190,000 people, thereby constraining 1.5 million managers with skills to make decisions based on the analysis of big data.”

What is Data Science?

The name and knowledge of data science may seem abstract, yet we interact with its outputs and product on a daily basis. When you are surfing the internet in search for information on the internet (Google), or asking seeking navigational information to know your destination, you are interacting with data science products. This discipline has been behind resolving some of our most common daily tasks for several years.

In the absence of data, beliefs are uninformed and decisions, in the best of cases, are based on best practices or intuition. The representation of complex environments by rich data opens up the possibility of applying all the scientific knowledge we have regarding how to infer knowledge from data. Data science is commonly defined as a methodology by which actionable insights can be inferred from data. The representation of complex environments by rich data opens up the possibility of applying all the scientific knowledge we have regarding how to infer knowledge from data.

These data could come in the form of customer database, residence address, sampling location, health record, school digital register, staff nominal roll and payment information and many more. Data science career applies almost every field of human endeavor.

Data Science Courses

Data Science Career entails an understanding of the following: computer science, mathematics, statistics, code programming especially in Python.

Data Scientist in Python: This involves developing competence in making the right inference and prediction from data using Python, SQL, and Machine Learning. This is a Dataquest career path — a sequence of interactive data science courses that’s designed to take you from total beginner to qualified data scientist. You’ll learn to write and run real code, all from the comfort of your browser window. This course is designed for beginners whose interest is to develop skills in Python programming. SQL queries, Data analysis and visualization, data mining, web scraping, APIs, probability and statistics, machine learning, deep learning, Jupyter Notebooks, and Git, Comand Line/Bash and many more.

Applications of Data Science:

• The knowledge of Data science can help us predict future stock prices
• It can as well be use to predict the value of real estate prices and value.
• It can be used to identify market and business opportunities.
• Use demographic data and SAT scores to assess testing bias
• It can be used to filter spam email messages.
• It can as well be used to build a system to reading hand written numbers.

Data Science Salary

Data science Career professionals earn as much as $100,560 in a year according to US Bureau of Labor Statistics. Howbeit, the experience, job title, industry, region and many other factor can influence their income. Entry level professional earn about $95,000 while mid-level staff earn $130,000. Highly experience staff can earn as high as $250,000 per annum.

Data Science Academy

Developing Data Science Career is not simple to achieve, but possible. This is because there are very few Universities that offer this course at first degree level. You need to advance your Bachelor degree in Computer Science or its related discipline for a Masters program in Data Science. There are some certification programs you can as well enroll for to leverage on that deficiency. Here is a list of some of the Universities offering this course at Master’s level.

• DePaul University‘s College of Computing and Digital Media
• Harvard University‘s John A. Paulson School of Engineering & Applied Sciences
• Carnegie Mellon University‘s School of Computer Science
• Columbia University‘s Data Science Institute
• Rutgers University – New Brunswick‘s School of Arts and Sciences
• Tufts University‘s School of Engineering
• New York University‘s Center for Data Science
• University of Minnesota – Twin Cities‘s
• University of Rochester‘s Goergen Institute for Data Science
• University of Washington‘s College of Science & Engineering

Data Science Interview Questions

Preparation is key if you are aiming at impressing your potential employer with your knowledge and experience. Your abilities and competencies must be visibly expressed in your confidence and ability to answer smart questions without stammering.

Here are a few questions we have outline for your preparation as you aim for the hottest job of the century.

• What do you understand by Data science and how can it enhance our productivity?
• Give us three reasons that make you unique for this job.
• What are the differences between supervised and unsupervised learning?

·        How is logistic regression done?

·        Explain the steps in making a decision tree.

·        How do you build a random forest model?

·        How can you avoid the overfitting your model?

·        Differentiate between univariate, bivariate, and multivariate analysis.

·        What are some of the steps for data wrangling and data cleaning before applying machine learning algorithms?

·        How to deal with unbalanced binary classification?

·        What is the difference between a box plot and a histogram?

·        What is cross-validation?

Career Advice for Future Data Science Professionals:

As you pursue a career in data science, never get to the status of over comfort. Aim higher and commit yourself to continuous self development. Enroll for short courses, further your degree courses and much more importantly participate in professional association and groups that will ensure great visibility for your career.