You might be curious about what an entry-level job in data science will look like if you are thinking of a career as a data scientist. The good news is that data scientists are in high demand and this trend is only expected to continue.
No matter where you are, data science is a highly sought-after job for employers worldwide. This is expected to increase as more companies collect data and seek out people to help them understand it.
What entry-level job in data science should you expect? Let’s take a look at the below and maybe you’ll be ready for a data science bootcamp.
Why Data Science is Important
Data science job opportunities are on the rise and will continue to grow according to almost every account. ZDnet reported that in 2021 DevSkiller ranked data science as the most sought-after tech skill, surpassing PHP and Python.
Glassdoor’s Job Market Report also shows that data analyst and data science are the jobs with the highest average salary growth across the United States. Glassdoor also ranks data scientist as the No. The 3 most popular job in the country, with an average job satisfaction score of 4.1 out 5 and more than 10,000 open jobs.
What is driving demand for data science jobs in the UK?
Tech companies, in particular, are collecting more data than ever before and trying to be as analytical as possible. Companies have a mountain data without data scientists. There is no way to present, analyze or find the data that can be used to market, sales, or any other department.
This is where data science comes in. Many estimates predict that data science jobs will outnumber web developers by the end this decade, with so many companies still playing catch-up. The median salary for a data scientist is already higher than many coding salaries.
Are you still convinced? Let’s take a look into the basics of data science.
What is data science?
As mentioned, companies are generating more data than ever before. Data scientists need a way to visualize that data and make business decisions based on it. Data scientists can use a variety of techniques to accomplish this.
How do data scientists do this? These are the five fundamental aspects of data science:
Data capture: This is the first step in data science when they start from scratch. It involves acquiring the data, extracting it to an easy-to-use medium, data entry and signal reception
Data maintenance: This is the next step in data sciences. Data warehouse or lake is a common term used in data science. It basically means a place where all acquired data can live. Data cleansing, staging, processing, as well as creating a data architecture are all aspects of maintaining data. This will help keep data companies organized and up-to-date.
Data processing: Data scientists work with stakeholders to determine what data should be captured and how it should be processed and viewed. This includes data mining, classifications, modeling, and summarization.
Data analysis: Data analysis can include confirming data, predictive analytics, regression, text mining and qualitative analysis. Many of these can be referred to as machine learning.
Data communication: Data scientists are responsible for communicating what they have learned to key stakeholders. This involves showing what was discovered in a visual medium such as Tableau or Looker, and helping coworkers make decisions based upon business intelligence.
Entry-level Data Science jobs
You won’t be able to do everything you want every day, just like any other career path. However, there are some roles that will help you learn the basics of data collection and visualization for companies. These roles include:
Machine Learning Analyst
This role will allow you to conduct statistical analysis, manage machine learning processes, and maintain artificial intelligence (AI). Cross-checking AI is a major part of machine learning analysts’ work. This ensures that the machine learning components are correct and provides accurate data.
A business analyst, unlike most data science roles will likely work with a company’s finance team. Business analysts at entry-level work alongside more experienced analysts to plan, budget, and evaluate business models.
A d data engineer is one of the most popular entry-level jobs in data science. They are responsible for managing and developing data feeds and pipelines. They spend their time fixing bugs and flaws within data systems to ensure accurate information is extracted for business purposes.
Every entry-level da