Data Analytics (STEM)

You can add these skills to your future application materials!

• Gain technical abilities and professional skills to help organizations leverage data to innovate practices and processes and inform decision-making
• Learn aspects of data science including data management and security, project management workflow, and business analytics
• Understanding of the various areas of data analysis as well as the industries in which it is used, and explore the types of professional roles that exist in the world of data
• Learn methods for diagnosing organizational problems in order to determine the data requirements to solve them
• Identify contemporary systems and technologies impacting the field of data analytics, including the cloud, AI, and machine learning
• Knowledge of data visualization tools and techniques that help data analysts communicate the results of their work in ways that make those results actionable

You can add these skills to your future application materials!

• Interpret business questions through a data lens
• Collecting and cleaning data
• Data visualization
• Communicating analytical results and recommendations to technical and non-technical audiences
• Python, SQL, Tableau, SAS and R
• Quantitative/qualitative data analytics methods
• Data analytics standards and policies
• Digital portfolio creation
• Real-world problem-solving skills and critical thinking skills

You can add these skills to your future application materials!

• Translate organizational needs and business problems into data analytics requirements to inform possible solutions and communicate them to technical and non-technical audiences
• Apply appropriate data analytics solutions, standards, and policies to meet the security, quality, storage, and privacy needs of organizations
• Collaborate in multi-functional teams on short and long term projects, providing the data analysis that helps inform decisions
• Gather, clean, interpret, and visualize data using industry tools and techniques most appropriate to the situation
• Use quantitative and qualitative data analytics methods in responding to a variety of situations that arise in the business environment

So you want to know work in data analytics, but there’s one thing bothering you. You don’t have any industry experience. Now, as you consider a big career change, you’re wondering: Is it really possible to get hired in data analytics with little to no experience in the field? The short answer is yes, it’s entirely possible—and yes, employers will be open to hiring you (even without any prior experience)!

To break into a skilled industry, you have to start somewhere. But how do you prove yourself when you haven’t yet earned experience on paper? Here are some ways you can find an entry-level data analytics-related role:

• Start with Internships, Volunteer Experiences, or Early Career Development Programs
  • Many tech companies offer data analytics internships or early career development programs specifically designed for students and recent graduates. These opportunities provide hands-on experience, mentorship, and the chance to work on real-world projects.
    • Ex. Early career development programs at NSA
  • Internships can be a valuable stepping stone to securing a full-time entry-level position within the company or gaining industry experience to enhance your resume.
  • Volunteer to join data science or data analytics related projects, like the ones provided by the National Student Data Corp. or DataKind.
  • Check out the “Gain Experiences” section on this page to browse real-world volunteer projects with real organizations!
• Gain Experience
  • Check out the “Gain Experiences” section on this page to browse real-world volunteer projects with real organizations!
  • Check out the “How To Gain Relevant Experience for your STEM Career Search” section on the STEM homepage.
  • Watch the entire 3 part webinar series videos, “Navigating Your Data Analytics Career Journey” where we highlight these tips and more.
• Explore “Feeder Roles”
  • Feeder roles are jobs outside of the data analytics sector that can serve as a pathway into the field. These positions cultivate key skills and knowledge that are transferable to data analytics. Common feeder roles include:
    • Financial risk analyst – This feeder role builds risk analysis and risk mediation skills. Like data analytics professionals, financial risk analysts use data to predict risks and recommend solutions. 
    • Security intelligence – Intelligence Analysts, Security Analysts and Background Specialists all play a critical role in organizations ability to proactively mitigate risks by studying large amounts of data and identify important statistics.
    • IT support– Help Desk Analyst professionals maintain, diagnose, and repair hardware and software systems—all helpful foundational data analyst skills.  
• Research & Explore Entry-Level Jobs
  • If you hope to work in this field, learning how to find entry-level positions could help you start your career!
  • You can start by researching the most popular entry-level data analytics related jobs, and see which align closest with your unique career goals and skills:
    • Business Analyst
    • Jr. Marketing Analyst
    • Data Analyst
    • Quality Assurance Analyst
    • Data Entry Clerk
    • Business Intelligence Analyst
• Utilize Your Network
  • Networking is another powerful tool for landing your first data analytics job. Reach out to friends, family, and acquaintances who work in your field of interest.
  • Also don’t overlook making a simple LinkedIn post or joining a LinkedIn community stating that you’re open to work and asking for help from your connections.
  • Lastly, attend job fairs and other events related to your industry. These events are a great opportunity to meet people who can provide valuable insights and help you connect with potential employers!
• Tailor Your Resume and Cover Letter For Each Application
  • Take the time to tailor your resume and cover letter to the job or internship you are applying for. Highlight your relevant skills and experience, even if it’s not directly related to the job.
  • Consider using a functional resume format that focuses on your skills and abilities rather than your work experience.
  • In addition, remember to always use keywords mentioned in the job description on your resume because many companies use AI software to match your resume with keywords found in job descriptions.
• Build A Strong Online Presence
  • Establishing a professional online presence can help employers discover you.
  • Maintain and update your LinkedIn profile, and participate in relevant online communities, and showcase your projects or contributions on platforms like GitHub.
  • This visibility can increase your chances of being noticed by potential employers and industry professionals.

Employers are eager to find data analytics students and graduates! Some experienced professionals find they are looking to make a new career move. Knowing how switching to a data analytics career can be beneficial can help you plan the next part of your professional life!

• Switching Careers – Advice for Career Changers
  • Transitioning to a career in data analytics should build on existing professional experience. In many cases, making a successful switch is a matter of refining specific skills, and highlighting transferable skills from your past experience.
  • Spend time researching the technical and soft skills your ideal data analytics-related job requires, and spend time updating your resume and applications to be sure you have noted all your current/newly acquired skills, relevant certifications, and transferable skills from your past experience.
• Explore “Feeder Roles”
  • If you are a mid-career professional looking to transition into the data analytics field, you may want to research feeder roles to get started. Feeder roles are jobs outside of the data analytics sector that can serve as a pathway into the field. These positions cultivate key skills and knowledge that are transferable to data analytics. Common feeder roles include:
    • Financial risk analyst – This feeder role builds risk analysis and risk mediation skills. Like data analytics professionals, financial risk analysts use data to predict risks and recommend solutions. 
    • Security intelligence – Intelligence Analysts, Security Analysts and Background Specialists all play a critical role in organizations ability to proactively mitigate risks by studying large amounts of data and identify important statistics.
    • IT support– Help Desk Analyst professionals maintain, diagnose, and repair hardware and software systems—all helpful foundational data analyst skills.  
• Research & Explore Entry-Level Jobs
  • If you hope to work in this field, learning how to find entry-level positions could help you start your career!
  • You can start by researching the most popular entry-level data analytics related jobs, and see which align closest with your unique career goals and skills:
    • Business Analyst
    • Jr. Marketing Analyst
    • Data Analyst
    • Quality Assurance Analyst
    • Data Entry Clerk
    • Business Intelligence Analyst
• Popular Data Analytics Jobs To Explore
  • As you begin considering career options, you might want to spend some time researching the various data analytics career paths out there and which aligns closest with your passions and skillsets.
  • While researching specific roles, you will want to consider researching some of the top companies looking to hire those with data analytics skills.
• Popular Data Job Boards To Explore
  • You are probably asking, where can you find jobs with great tech companies? Well, job boards are one place you can start!
  • We put together this list of the best data job boards so you can quickly and easily find jobs to apply to.

As a you pursue data analytics jobs, employers may be expecting that you have not only the experience in the field, but the technical knowledge and certifications to prove your expertise! This involves a demonstrated ability to manage complex projects and lead large teams before applying for advanced leadership-level data analytics roles.

• Technical Knowledge for Data Analytics Majors
  • There are a number of technical skills that are required for a data analyst job, including a knowledge of SQL, various programming languages, and data visualization software.
  • When creating a resume or applying for a new role, its important to highlight the relevant skills that demonstrate your expertise and qualifications in the field:
    • SQL
    • Excel
    • Statistical Programming: Python, R
    • Data Visualization: Tableau, PowerBi, Plotly, Bokeh, Infogram
    • Data Cleaning & Data Manipulation
    • Machine Learning
• Certifications to Explore
  • Another popular way for data analytics professionals to demonstrate their skills in data analysis to potential employers is via certifications.
  • Its important you take the time to first explore certification types and find options to find the best fit for your unique career goals!
    • Certified Analytics Professional (CAP)
    • Certified Business Intelligence Professional (CBIP)
    • Associate Certified Analytics Professional (aCAP)
    • Tableau’s Desktop Certified Associate
    • Microsoft’s Power BI Data Analyst Associate
    • AWS Certified Data Analytics