Commonly Answered Questions about Data Science in 2023 -Part 3
Tags: data, datascience, webdev, javascript
Published: 2022-12-26 11:37:18

## Where can I find the best Data Science Job?
The first site immediately comes to mind is the free job listings website. It is possible to use all job sites (LinkedIn Indeed, LinkedIn, Google for Jobs, SimplyHired, AngelList, Hired and so on.) as well as data science-related niche jobs boards ( KDNuggets, DataJobs, Amazon Jobs, StatsJobs and many more.). There are websites to help you find remote positions: Upwork, Remote, and JustRemote. We Work Remotely. You can also look into specific job boards, like outer join, which is solely focused on remote jobs within the field of data science.

Getting in touch with a business of interest is also possible. Go to the official site of their company, and explore the home page, careers webpage, and contact information. Explore their mission, values, and business model, and then consider whether you would be an ideal match for the company. With these details, you can mail them an email with your resume for data science included. While it is more time-consuming, it is beneficial than the previous one because it allows you to display a genuine interest in the organization and be different from other applicants.

To increase your chances of securing jobs in data science quickly, it is useful to go to data science events or events (both online and online) and make connections with the most relevant people on social networks and interact with professionals from the field and other learners through specialized communities of data science.  If you want to go beyond this article & dive deeper into Data Science, you can definitely master from [Data Science with Python Certification.](https://www.edureka.co/data-science-python-certification-course)
 
 

## What skills and qualities do Employers Want in the Data Scientist?
The most basic technical abilities that employers generally look for in data scientists are:

- A good grasp of Python as well as R (especially the most well-known data science modules in this language)
- proficiency is a key component of SQL
- the ability to work on the command line
- understanding of statistical concepts
- cleaning and wrangling data analysis and visualization abilities
- Predictive modelling, model estimation with machine learning and deep-learning algorithms
- working with data that is not structured
- Storytelling
- web scraping
- debugging
It doesn't mean you'll need all these skills to succeed in any data science job. To know what each company is looking for in a data scientist, you must read the job description and create lists of the requirements for the technical skills and equipment they need.

For the abilities of data scientists, The most sought-after skills include:

- critical thinking
- team working
- Knowledge of the business domain
- efficient communication
- the process of making a decision
- Multitasking
- Flexibility
- curiosity
- Creativity
- ability to meet deadlines

## What should I keep in mind when looking for a Data Science Job?
The first step is to create a portfolio of work. This is crucial for applicants who do not have actual experience working in this area. The portfolio should contain the projects you worked on as part of your data science course or Bootcamp course. Also, consider creating 3 or 4 additional projects to make your portfolio distinctive. If you are a data scientist at the entry-level or someone who is a career changer, It is fine to start with a portfolio that includes projects that cover a variety of subjects and methods. If you are applying to the job you are interested in, make sure you know what of your work highlights the top of the skills needed for that job.

The next important aspect is your resume for data science. Before you apply for various jobs, you should consider making a master copy of your resume in which you list all the relevant information about the education you have received, your work experiences (even when it isn't data-related), courses, boot camps or projects, as well as soft and technical skills as well as any other accomplishments which could be pertinent in some way. Be assured that the resume you've created is lengthy or consists of several sections and subsections. If you ever want to submit an application for a specific job in data science, you can use your resume master as a base. Create a duplicate of your resume, remove any redundant information and sections, and then customize your resume to fit the post based on your job's description. Remember that modifying your resume for each job is essential to your job search process. If you need more advice on writing an impressive, professional-looking resume for data science, then you will find the following article beneficial.

The last thing you need to know is the possibility that you will not immediately get employment in data science. If this occurs, don't be discouraged. It's normal to experience this if your job search is lengthy. Don't let rejections eventually annoy you and cause you to start believing that you're not an expert. Instead, work on improving your data science abilities and look at the areas that can be improved on your resume, project portfolio, and the application process as a whole. If you receive feedback from one of the companies you are applying to, Make the most of this feedback by working on the areas you have highlighted as areas of weakness.