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Entry Level Data Analysis Jobs in Washington (NOW HIRING)

VivSoft Technologies

Business Data Analyst

Herndon, VA · Remote

We are seeking a detail-oriented and proactive Business Data Analyst I to support documentation ... analysis, and administrative functions across various business systems. This entry-level role ...

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Entry Level Data Analysis information

What are some common challenges entry-level data analysts face when starting out, and how can they overcome them?

Entry-level data analysts often encounter challenges such as learning new data tools, understanding unfamiliar datasets, and translating business questions into analytical tasks. It's common to feel overwhelmed by the variety of software (like Excel, SQL, or Python) and the pace of real-world projects. To overcome these hurdles, new analysts should proactively seek mentorship, participate in team discussions, and take advantage of online resources or internal training. Regular collaboration with colleagues and asking clarifying questions can help build confidence and ensure successful project contributions.

How to get hired as an entry-level data analyst?

To get hired as an entry-level data analyst, candidates should develop foundational skills in data analysis tools like Excel, SQL, and Python or R, and build a portfolio of relevant projects. Earning certifications such as Microsoft Data Analyst Associate or Google Data Analytics can improve prospects, along with gaining internship experience or completing relevant coursework. Strong communication skills and the ability to interpret data for non-technical audiences are also important.

Can I be a data analyst with no experience?

Entry level data analyst positions often do not require prior professional experience, but having skills in Excel, SQL, or data visualization tools can improve your chances. Many employers value relevant coursework, certifications, or internships that demonstrate your ability to analyze data effectively.

What is an entry level data analyst?

An entry level data analyst is a professional who collects, processes, and performs basic analysis on data to help organizations make informed decisions. They typically work with tools like Excel, SQL, or data visualization software to organize and interpret data sets. Entry level analysts focus on tasks such as cleaning data, creating reports, and identifying trends, usually under the supervision of more experienced analysts. This role is ideal for recent graduates or individuals starting their career in data analysis.

Is 40 too late for data science?

Entry level data analysis roles are accessible at any age, including at 40 or older. Success depends on acquiring relevant skills such as proficiency in Excel, SQL, and data visualization tools, as well as building a strong portfolio and gaining practical experience. Age is less important than skills, continuous learning, and adapting to industry tools and methods.

What are the key skills and qualifications needed to thrive as an Entry Level Data Analyst, and why are they important?

To thrive as an Entry Level Data Analyst, you need foundational knowledge in statistics, data interpretation, and a relevant degree such as in mathematics, economics, or computer science. Familiarity with tools like Microsoft Excel, SQL, and data visualization platforms such as Tableau or Power BI is typically required. Strong analytical thinking, problem-solving abilities, and clear communication help you extract meaningful insights and present findings effectively. These skills are crucial for transforming raw data into actionable information that supports informed business decisions.

Is AI replacing data analysts?

AI tools are automating certain repetitive tasks in data analysis, such as data cleaning and basic reporting, but they do not replace the need for skilled data analysts. Entry-level data analysis roles still require critical thinking, domain knowledge, and interpretation skills that AI cannot fully replicate. Professionals who develop expertise in data visualization, programming, and statistical methods remain valuable in the field.

What is the difference between Entry Level Data Analysis vs Data Analyst?

AspectEntry Level Data AnalysisData Analyst
Required CredentialsAssociate's degree or relevant certificationBachelor's degree often preferred
Work EnvironmentInternships, entry-level roles, training programsFull-time positions in various industries
Employer & Industry UsageStart of career, learning phaseMid-level roles, more responsibilities
Common Search & Comparison IntentUnderstanding entry-level opportunitiesAdvancement and skill development

Entry Level Data Analysis roles are designed for beginners with minimal experience, focusing on learning foundational skills. Data Analysts typically have more experience, handle complex data projects, and contribute to strategic decision-making. The main difference lies in experience level, responsibilities, and career progression.

What are the most commonly searched types of Data Analysis jobs in Washington? The most popular types of Data Analysis jobs in Washington are:
What are popular job titles related to Entry Level Data Analysis jobs in Washington? For Entry Level Data Analysis jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Analysis jobs in Washington look for? The top searched job categories for Entry Level Data Analysis jobs in Washington are:
What cities in Washington are hiring for Entry Level Data Analysis jobs? Cities in Washington with the most Entry Level Data Analysis job openings:
Entry Level Data Analysis jobs near you
Infographic showing various Entry Level Data Analysis job openings in Washington as of June 2026, with employment types broken down into 75% Full Time, 19% Part Time, 1% Temporary, and 5% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Scientist - Multiple Levels (TS/SCI with Poly Required)

Red Alpha Careers

Annapolis Junction, MD

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

Job description

A little about us:
The Red Alpha Data Science practice grew out of Red Alpha's reputation in Software and System Engineering with our Department of Defense clients. As sometimes happens, customers who trust our expertise in adjacent areas asked Red Alpha to assist with some of their burgeoning Data Science problems.

Culturally, it probably suffices to say that we take our work seriously, but not ourselves. Our leaders have spent time in the trenches and have cursed daylight savings time changes and trailing whitespace as many times as you have. We like to say that we spend 80% of our time cleaning the data...and 20% of our time complaining about cleaning the data. Joking aside, our voices matter, and it is easy to see how our decisions affect the Data Science practice and Red Alpha as a whole. We have a clear vision of where we are headed.

Our team takes a pragmatic approach to Data Science, defining it loosely as the intersection of technical expertise, business acumen, and soft skills to solve business problems with data. We spend a lot of time trying to understand the problem before we set about building a solution, and we prefer lower tech useful solutions over shiny algorithms and dust on the shelf. Did we mention we're pragmatic? We have a diverse set of skills across our team, and whether you are a traditional Data Scientist (whatever that means...), an Applied Research Mathematician, a Database Engineer, a Full Stack Developer, or something else in that neighborhood, if you have a knack for picking apart data to make sense of it, we would enjoy having a conversation with you.
A day in the life:
In this role, you will provide support and related services to the implementation of enterprise data representations in various mission domains. You will be performing end-to-end systems engineering for data flows from the perspective of data format modeling, data mapping, and support to implementers and mission customers. This role requires strong software and systems engineering expertise from cradle to grave with limited, high-level direction, in the areas of:
  • Enabling and growing existing automation efforts, adding additional data streams, and driving forward data transformation efforts.
  • Focusing on the sponsor's business analytics, metrics collection, and analysis efforts. The sponsor's management team requires a data scientist to characterize the sponsor's workforce, workforce productivity and output, and the value of collection to the workforce.
  • Possessing an instinctive aptitude to leverage information and knowledge sharing networks and navigate conflict in a way that fosters constructive outcomes.
What you bring to the table:
Now on to the fun of formal requirements - we have to apologize in advance for the corporate-speak here, but just hold your breath for a few lines and everything will be okay. We are actively hiring data professionals for roles across a broad range of skill levels and projects. Our goal is to find the best fit for you so please note that if you apply to one of them and we see a fit elsewhere we will let you know. So do not worry about applying initially for every position you might be interested in.

All of our data scientists need the following skills:

  • Proficiency with a scripting language such as R or Python
  • Experience with data science techniques and algorithms such as classification, clustering, random forests, deterministic forests (jk), hierarchical modeling, deep learning, Markov Chain Monte Carlo, and others. Note that you do not need to have all of these (we hope you enjoyed our random smattering of techniques...!) but you should be comfortable and capable with several of them and know some others not on this list.
  • A B.S. Degree in Data Science, Mathematics, Computer Science or related field.
  • For entry-level data scientists, 0-3 years of experience on Data Science projects.
  • For mid-level data scientists, 3-6 years of experience on Data Science projects.
  • For senior-level data scientists, at least 6 years of experience on Data Science projects with at least 3 years of experience managing teams.
  • A TS/SCI with Polygraph security clearance.

For this particular role, you will also need:

  • A broad range of knowledge including information technology, requirements, technical architecture analysis (e.g., understanding data flow diagrams, system architecture diagrams, etc.), and an understanding of functional and system analysis.
  • Knowledge of multiple development methodologies, Agile (Scrum & Kanban), etc.
  • An understanding of SIGINT

These are important skills to have, but not necessarily mandatory:

  • Exceptional interpersonal skills. You know, as in you might not be at the top of the list to be a game show host, but you do like people and enjoy solving problems jointly with your colleagues.
  • Experience with Java, C, or other compiled languages
  • Comprehensive knowledge of Saturday Night Live sketches (just kidding)
  • Experience with SQL/NoSQL, Spark, Hadoop
  • Familiarity with Javascript and Scripting
  • Familiarity with Docker, GitLab, and React
The total package:
Our total compensation package was strategically designed with our members in mindwith the intention to: reward our members for their hard work and commitment to our customers' missions; allow members to share in Red Alpha's success as wecontinue to grow and expand our footprint; provide long-term career opportunities through stability and internal mobility; and provide the resources our members need to support themselvesandtheir dependents in the form of a robust benefits package. Our total compensation package includes a competitive base salary andbenefits such as health, life/disability, 401k, paid time off,professional development, and generous bonus programs. Please visit ourbenefitstab for additional information.
Salary Range:
  • Disclosed pay ranges are a general guideline, and are not a guarantee of a final salary or compensation. Our approach in determining final salaries takes into consideration a number of factors such as education, certifications, total years of relevant professional experience,actual level of expertise, and the responsibilities of the role itself.
  • Based on the outlined roles, responsibilities, and requirements, the projected pay range for these positions are:
    • Entry-level: $95,000 - $135,000
    • Mid-level: $110,000 - $155,000
    • Senior-level: $135,000 - $235,000
Some of our additional perks and benefits include:
  • Retire soonerthan planned: Get closer to retirement with up to 10% in 401k contributions, immediately vested.
  • Have a career AND a life:Enjoy up to 5 weeks of leave (25 days of personal time off) and 11 paid floating holidays.
  • Stay at your best:As a member, we'll pay 100% of your premiums for comprehensive health, dental, and vision insurance. We'll also pay the majority of the premiums for your family. Let's not forge free access to a fully equipped state of the art gym!
  • Keep current on new technologies and technological advancements: $5250 per year towards ongoing education, trainings, certifications, and maintaining professional memberships.
  • Dress in style: Spend up to $300 per year on company branded merchandise featuring top quality brands such as Under Armour, Nike, Carhartt, YETI, etc.
  • Enjoy the culture: Attend fun company events throughout the year such as our Oktoberfest, summer picnic, and annual holiday party! These are all in additon to your team events which may include happy hours, baseball games, snowboarding, RenFest, and more!
Every day, our elite customers are pushing through "the grind" to defeat the enemy, even putting their lives on the line for our freedom. Rise to the occasion with us to deliver engineering excellence, to match their dedication to this nation. Join us as webring digital transformation to the fight!
Employment Type: Full-Time

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