Data Science Career Opportunities: Your Guide To Unlocking Top Data Scientist Jobs

In a world that generates 2.5 quintillion bytes of data every day, a professional who can organize this large amount of data to deliver business solutions is truly a leader! There is a lot of talk about why Big Data continues here and why Big Data Analytics is the best business venture. Based on what has already been written and said, we can discuss Data science career opportunities and why ‘Data Scientist’ is an attractive career title for the 21st century.

Data Science Career Opportunities

According to a data scientist at the Harvard Business Review, “Big Data is a highly professional professional with the training and passion to make discoveries in the world.” So it is not surprising that data scientists are experts in the fields of Big Data Analytics and IT.

While experts predict that there will be 40 gigabytes of data (source) by 2020, data science career opportunities will only be filmed through the roof! The shortage of skilled professionals in the world who are increasingly turning to decision-making data has led to a huge demand for data scientists in startups and well-established companies.

A McKinsey Global Institute study predicts that by 2018, the United States alone will face a shortage of approximately 190,000 experts with in-depth analytical skills. While the big data wave shows no signs of slowing down, data companies around the world should be hired to manage their business-sensitive big data.

Data Scientist Salary Trends

The Glass door report reveals that data scientists are vying for the best jobs in the United States. According to a report, the average salary of a data scientist in the United States is $ 91,470 and $ 622,162, and more than 2,300 jobs are published on the site.

According to Indeed.com, the average data scientist salary for job vacancies in the United States up to May 2019 is 80% higher than the average salary for all job posts nationwide.

Data Scientist Job Roles

A data scientist wears several hats in his workplace. Data scientists are involved not only in business analysis, but also in the creation of data products and software platforms, as well as visualization and machine learning methods.

Some Important Data Scientist Job Topics :

• Data / Analysis Manager
• Business Intelligence Manager
• Data Analyst
• Business Analyst
• Data Manager
• Data Scientist
• Data Architect

Hot Data Science Skills

Combining coding skills with statistical knowledge and the ability to think critically creates the arsenal of a successful data scientist. Some Data Scientist Skills Needed to Get the Best Career Opportunities in Data Science :

• Proficiency in Deep Learning Frameworks: TensorFlow, Keras, Pytorch
• Creative Thinking & Industry Knowledge
• Databases: SQL and NoSQL
• Machine Learning and Neural Networks
• Programming Languages: R/Python/Java
• Statistics and Applied Mathematics
• Working Knowledge of Hadoop and Spark

How to Become a Data Scientist (Step-By-Step) in 2021

Data science is currently the most exciting field and is in serious demand by data scientists. For good reason — data scientists do everything from creating self-driving cars to captioning pictures automatically. Considering all the interesting applications, data science means the most demanding job.

Question Everything

The appeal of data science is that you have to answer interesting questions with real data and code. These questions are “Can I predict if any flight will arrive on time?” “How much does America spend on education per student?”. You need to develop an analytical mindset to ask and answer these questions.

The best way to cultivate this mindset is to start it with news articles. Find articles like these that make you better and find out if sugar is really bad for you. Think :

• How to draw their conclusions based on the data they discuss
• How to design a study to explore further
• Questions you would like to ask if access to basic data is possible

Learn The Basics

Python is a programming language with standard syntax that is recommended for beginners. Fortunately, it provides the skills to do tasks related to more complex data science and machine learning, such as in-depth study.

Many people worry about choosing a language, but the important things to keep in mind are :

• Data science is not about tools, it is about answering questions and running business value.
• Learning ideas is more important than learning syntax.
• You create projects and share them in a real data science role, learning this way will give you a start.

Build Projects

As you learn the basics of coding, you should start developing programs that answer interesting questions and demonstrate your data science skills. Plans do not have to be complicated.

For example, you can analyze Super Bowl winners to find patterns. It’s important to find interesting datasets, ask questions about the data, and then code those questions with the answers. If you need help finding databases, check out this post for a list of good places to find them.

When making plans, keep this in mind :

• Data cleaning is the mainstay of most data science jobs.
• Linear regression is the most common machine learning technique.
• It all starts somewhere. Even if you think what you are doing is not enjoyable, you need to do it.

Share Your Work

Once you’ve created a few projects, you need to share them with others! It’s a good idea to upload them to GitHub for others to see. You can read a good post here about uploading projects on Git Hub, and learn more about linking to a portfolio. Uploading projects:

• Motivate yourself to think about how to best present them, which you will do in a data science role
• Allow your colleagues to see and comment on your plans
• Allow employers to see your plans

Learn From Others

Once you’ve started creating an online presence, it’s a good idea to start interacting with other data scientists. You can do this in person or in online communities. Some good online communities:

• Datascience
• Data science slack
• Kaggle
• Quora

Personally when I was studying I was very active in Kaggle and Quora, which helped me a lot. The best way to do this is to engage in online communities:

• Find others to learn from
• Improve your profile and find opportunities
• Strengthen your knowledge by learning from others
• With meetups you can interact with people in person. Individual interventions will help you meet and study experienced data scientists in your area.

Push Your Boundaries

Now Companies want to hire data scientists who can find key statistics that save money or make customers happy.

• You should use the same process for learning — look for new questions to answer, answer difficult and complex questions.
• If you do not look back at your plans a month or two ago and feel ashamed of something you did, your boundaries will not move forward enough.
• You need to make strong progress each month that will be reflected in your work.

Data scientist qualifications

• Must have a strong command of technical expertise related to working data scientists, including Python or R programming, writing questions in SQL, building and improving machine learning models in their language, and some “workflow” skills such as kit and command line.
• Data scientists need strong problem solving, data visualization, and communication skills. When a data analyst is often asked a question to answer, a data scientist is expected to explore the data and find relevant questions and business opportunities that others may be missing out on.
• Although it is possible to find a job as a data scientist with no prior experience, working as a data analyst before becoming a data scientist is the most common path for interested data scientists with no relevant professional experience.

Data Scientist Educational Requirements

• Most Data Scientist roles require at least a Bachelor’s degree. Degrees in technical fields may be preferred, as are advanced degrees such as PhDs and masters, but advanced degrees are usually not strictly required (even when they claim to be job postings).
• What employers pay the most attention to is your ability. Applicants with minimal advanced or technical related degrees can fill this gap with an excellent project portfolio, which demonstrates their advanced skills and experience in performing related data science tasks.

What skills are required to become a data scientist ?

Specific requirements vary slightly from job to job, and more specific roles develop as the industry matures. However, in general, the following capabilities are expected for any data science role :

• SQL
• Data Visualization
• Communication
• Programming in Python or R
• Building and Optimizing Machine Learning Models
• Solid Understanding of Probability and Statistics

Most of the time, machine learning will focus on a role in a specific subdomain. Each data scientist is expected to be familiar with the basics, but one role may require more in-depth experience with Natural Language Processing (NLP), while another may focus on developing a product-ready prediction algorithm.

Is it hard to become a data scientist ?

• You should expect that you will be challenged in your journey to become a data scientist. Achieving this role requires extensive programming skills and statistics in addition to strong communication skills.
• Anyone can learn all these skills, but you need strong motivation to move yourself through difficult moments.
• Choosing the right site and approach to learning can make the process easier.

How many years does it take to become a data scientist ?

• This will be different for each person. In DataQuest, most of our students report that they have achieved their learning goals within a year or less. How long the learning process will take depends on how much time you allow.
• Likewise, the length of the job search process will vary depending on the projects you have built, your other qualifications, your professional background and more.

Is data science a good career choice ?

• The demand for data scientists is huge, and the world is generating so much (increasingly) data every day.
• We are not saying there is a crystal ball or we do not know what the future holds, but data science is a fast growing field with high demand and high salaries.

What is the data scientist career path ?

• Many data scientists actually start their data careers as data analysts and move into data science roles through internal promotion or job changes.
• From there, more experienced data scientists can search for senior data scientist roles.
• Experienced data scientists with management skills can move on to the roles of Director of Data Science and similar director and management level roles.

What salaries do data scientists make ?

• Salary varies greatly depending on the applicant’s location and experience. However, on average, data scientists pay very comfortable salaries.
• The average data scientist salary in the United States will exceed $ 120,000 per year by 2020.