Super practical! Learn this, and you’re the next data science guru

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Data scientist is one of the hottest jobs on the market right now, and demand is only growing. Especially today, it seems to be growing faster than the actual number of data scientists.

One in 10 people want to work in data science.

Now is the perfect time to change career intentions and become a data scientist.

Now or never, this article will show you how to do it.

Let’s get started

What is a data scientist?

Data scientists are experts with deep expertise in data, algorithms, and data visualization. Being a data scientist requires the ability to work in a team, understand data structures, analyze data, design and create charts and graphs, and write concise code.

What a data scientist does

The job of a data scientist is to develop and analyze data, and then analyze that data to generate insights. These insights can be applied in a variety of ways, such as in various business decisions. And is often used to advise on new products or services or to help develop business cases. Data scientists work on a variety of different data science topics, such as:

Business Intelligence, Network analytics, natural language processing, social media analytics, predictive analytics, machine learning, data mining, etc.

Check out LinkedIn, AngelList, and other sites to find lists of key positions and how to apply for them. On these websites, you can browse job listings in your area.

How much do data scientists earn?

Data scientist is one of the hottest jobs in the industry right now, and it comes with a lot of perks. They earn between $120,000 and $180,000 a year. Software developers, by contrast, earn between $110,000 and $135,000.

Of course, the salary of a data scientist depends on the role, but they typically work in analytics or machine learning, and often work with large data sets.

They need to have excellent analytical skills, programming or database experience, and strong writing skills.

What it takes to be a data scientist

Data scientists are in high demand, so if you are interested in this type of job, you need to have a comprehensive set of skills.

Some of the skills required include:

– Excellent analytical skills, including the ability to understand data

– Good project management skills, including ability to plan and manage projects and ability to communicate with others

– Good communication skills, writing clearly and concisely

– Be aware of the importance of data integrity and privacy issues, as well as the importance of users

– Excellent quantitative skills, including the ability to use data to gain insight and communicate results clearly

– Ability to understand complex information and interpret results

– Critical thinking and problem solving, whether from the perspective of understanding the big picture or making specific decisions about how to solve a particular problem

Technical skills required by data scientists

From a technical point of view, here are a few other competencies — especially when applying for non-entry-level positions:

– Proficient in Excel, SAS, R or Python (Excel is a programming language)

– Machine learning experience

– Experience with databases (such as relational or NoSQL databases)

– Experience in data visualization

– Strong technical or computer science background

– Ability to learn quickly

In addition, data scientists often work in teams, which means a lot to learn quickly.

It’s not all about data, it’s also about information, so you need to be an active learner if you want to develop the skills you need to succeed in this industry.

Three steps to becoming a data scientist

Now, something very practical:

1. Build a repository on GitHub and start an open source project. You can take a data set from Kaggle and build something around it. It’s usually easier to categorize problems. It’s a great way to hone your skills and show your professionalism to potential employers.

2. Join data science groups and machine learning groups on Facebook or LinkedIn. Try to find meetings and conferences that they have in your area and join them to meet more people. It’s always a good thing to have someone to mentor.

Write more code! Ultimately, data science is a practical skill. Share your code on social media — and update your LinkedIn profile to have a better chance of landing a job.

Good luck to you all! Be the person you want to be — the master of data science.

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