Essential Steps to Start Your Career as a Data Scientist

Are you constantly asking yourself: 'How can I break into the Data Scientist field?'. 

If you're feeling overwhelmed and unsure where to start on this career path, you're not alone. Aniday is here to support you!

We’ll go over the essential stages in this guide to help you navigate the way to a Data Scientist career by detailing the educational pathways and providing an overview of salary expectations for this role. 

The Step-to-Step Roadmap to a Data Scientist Field

Step 1: Pursue a Bachelor’s Degree

First thing first, education.

A bachelor's degree in Computer Science, Data Science, Statistics, Information Technology, or Data Analytics is necessary to work in this field.

A research of 365 Data Science into 1,000 data science job postings for 2024 reveals that bachelor’s degrees are becoming more and more valued. 24% of these listings specified a preference for PhDs, 30% for master’s degrees, and 20% for bachelor’s degrees. This pattern demonstrates how this field’s employers are requesting more diverse qualifications.  

Step 2: Improve your skills

Balance your technical and non-technical skills if you want to succeed. Examine machine learning, data analysis, big data technologies, data visualization, and database administration from a technical standpoint. You should master key programming languages as well, like SAS, R, SQL, and Python. 

Alongside, improving your non-technical abilities namely project management, communication, flexibility, and time management. 

This all-encompassing strategy will lead you to success in this industry. 

Step 3: Attend Online Courses and Gain Certificationsnbsp;

The following are some credible online courses that can help you pursue your ideal profession as a data scientist:

• Certified Analytics Professional (CAP)
• DASCA's Principle Data Scientist certification
• Data Science Council of America (DASCA) Senior Data Scientist (SDS)
• Google Data Machine Learning
• IBM Data Science Professional Certificate
• Microsoft Certified Azure Data Scientist Associate certification
• Open Certified Data Scientist certification (Open CDS)
• SAS Big Data Professional certification
• SAS Certified Advanced Analytics Professional
• SAS Data Science Certification

Because education has undergone a radical change in the digital age, particularly with the emergence of online Data Science courses, here are some crucial benefits of taking online courses:  

• Variety of Options: you can simply locate classes that align with your unique requirements and interests, giving you access to a top-notch education from your home.
• Networking Opportunities: Through discussion forums and group projects, you can connect with a global community of learners, expanding your network and gaining diverse perspectives.
• Career Advancement: These courses arm you with new skills and knowledge, often culminating in a certificate that enhances your resume.

Step 4: Apply for Internships

After acquiring the fundamentals of data science, you might want to apply for internships to get your career started. Key roles to explore include: 

• Business Intelligence Analyst
• Data Analyst
• Data Engineer
• Statistician

Some tips on applying for internships:

Here are some tips to boost your chances of securing an internship in Data Science:

• Apply early: Internships are competitive, so aim to submit your application well before deadlines, especially for summer internships. Early applications give you time to refine your materials.
• Cast a wide net: Apply to multiple internships to increase your chances of success in a competitive field like data science.
• Showcase your skills: Build a portfolio showcasing your past projects or work samples to demonstrate your abilities.
• Utilize your network: Leverage professional contacts to discover internship opportunities and seek advice on improving your application.
• Prepare recommendation letters: Request recommendation letters early from lecturers or professionals who can vouch for your skills and character.
• Customize your application materials: Tailor your resume and cover letter for each internship to highlight relevant skills and experiences effectively.

Step 5: Apply For Data Science Entry-Level Roles

Once you've laid the groundwork in data science, you can progress towards entry-level roles such as:

• Data Scientist
• Data Analyst
• Data Engineer

Building your expertise, honing your skills, and gaining experience in these positions will elevate you into a sought-after data science professional.

Here are some tips to help you choose a suitable company to work for:

1. Culture and environment:  Look into how they promote collaboration, communication, and innovation and assess their support for learning, development, and feedback. You should seek a company that fosters a positive, inclusive culture and offers a flexible environment conducive to work-life balance and well-being.
2. Projects and domains: Explore the types, scopes, and complexities of their projects, as well as the industries they serve. You should look for opportunities that offer diverse and challenging projects, enhancing your skills and portfolio in different data science applications.
3. Tools and Technologies: Choose a company that employs modern tools, keeps pace with industry trends, and supports your growth in efficiency, productivity, and skills development. This prepares you to excel in data science by handling complex tasks and staying ahead of industry advancements.

Step 6: Advance with a Master’s Degree

As you build on your skills and experience gained from your bachelor's degree in a data science role, take the next step to deepen your expertise.

Embark on a master's degree in data science to gain advanced skills and propel your career forward.

Salary of Data Scientists based on their experience level

Data Scientist’s salaries vary based on their expertise, skills, and the company size they work in. Glassdoor reports that the average annual income for data scientists stands at $112,794, derived from a dataset of 18,000 professionals in this field. 

One of the key factors affecting your pay as a data scientist is years of experience. Here's a summary:

• Entry level with 1-4 years of experience: $98,000 per year
• Middle level with 5-9 years of experience: $113,000 per year
• Senior level with 10-19 years of experience: $ 124,000 per year

End Note:

Investing in your skills and following these essential steps can pave the way for a rewarding career as a data scientist. 

Remember, continuous learning and practical application of knowledge will be your greatest assets in this competitive recruitment landscape. 

As the industry's top recruitment service, we link top Data Scientist talents at all levels with domestic and international enterprises. 

👉Visit more on our website and see how Aniday can help you navigate the challenging Data Scientist landscape.

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