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Entry Level Data Science Training Jobs (NOW HIRING)

Noblesoft Solutions

Data Scientist

Jacksonville, FL · On-site

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to ... model training Executing projects involving analytics Identifying data patterns and trends ...

State Farm

Lead Data Scientist - Gen AI

Bloomington, IL · On-site

It also hosts centers of excellence for natural language processing, experimental design, generative AI, & data science training/research. At State Farm, we believe in fostering professional growth ...

Altagrove LLC

Data Science

Norfolk, VA · On-site

Conduct data exploration, feature engineering, model training, validation, testing, and performance ... Strong proficiency in Python and experience with modern data science and engineering frameworks.

Noblesoft Solutions

Data Scientist

Jacksonville, FL · On-site

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to ... training • Executing projects involving analytics • Identifying data patterns and trends • ...

Northern Trust

Sr. Data Scientist

Chicago, IL

$114K - $194K/yr

Plan and execute data science training sessions and hackathonsWork with external parties (vendors, universities, etc.) to incorporate new techniques and tools into the data science labSolves complex ...

Northern Trust

Sr. Data Scientist

Chicago, IL · On-site

$114K - $194K/yr

... data science training sessions and hackathons • Work with external parties (vendors, universities, etc.) to incorporate new techniques and tools into the data science lab • Solves complex ...

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How much do entry level data science training jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for entry level data science training in the United States is $19.47, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

What is entry level data science training?

Entry level data science training is a program or course designed to introduce beginners to the fundamental concepts, tools, and techniques used in data science. These trainings typically cover topics such as data analysis, statistics, programming (often in Python or R), and the basics of machine learning. They are intended for individuals with little to no prior experience in data science and help prepare participants for entry-level roles or further study in the field.

What are the key skills and qualifications needed to thrive in entry level data science training?

To thrive in Entry Level Data Science Training, you need a solid understanding of statistics, basic programming (often Python or R), and foundational data analysis concepts, typically demonstrated through relevant coursework or a degree in a quantitative field. Familiarity with data analysis tools like Jupyter Notebooks, Excel, and introductory machine learning libraries is important, as well as exposure to version control systems like Git. Strong problem-solving skills, curiosity, and effective communication make trainees stand out in collaborative and learning-focused environments. These skills and qualities are crucial for building a successful data science career and effectively translating data insights into actionable outcomes.

What can I expect from the team structure and mentorship opportunities during entry level data science training?

During Entry Level Data Science Training, you will often find yourself working as part of a collaborative team that includes experienced data scientists, analysts, and sometimes software engineers. Many training programs and entry-level positions offer structured mentorship, where senior team members guide you through technical challenges and best practices. Regular feedback sessions and pair programming are common, helping you quickly build practical skills. You'll also likely participate in group projects, fostering teamwork and exposing you to real-world data problems.

What is the difference between Entry Level Data Science Training vs Data Analyst?

AspectEntry Level Data Science TrainingData Analyst
Required CredentialsBasic understanding of statistics, programming, and data tools; often includes certifications or coursesTypically requires a degree in statistics, mathematics, or related field; may include certifications
Work EnvironmentTraining programs, online courses, workshops; often self-paced or instructor-ledOffice setting, working with data visualization, reporting tools, and databases
Employer & Industry UsageUsed by individuals seeking entry into data science roles; employers value foundational skillsEmployed across industries for data reporting, analysis, and business insights

Entry Level Data Science Training provides foundational skills and certifications to prepare individuals for data analysis roles. Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While training emphasizes learning tools and techniques, data analysts apply these skills in real-world work environments. Both roles are essential in data-driven industries, but training is a stepping stone toward a full data analyst position.

What are the most commonly searched types of Data Science Training jobs?

The most popular types of Data Science Training jobs are:

What states have the most Entry Level Data Science Training jobs?

States with the most job openings for Entry Level Data Science Training jobs include:

Entry Level Data Science Training jobs near you

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

Red Alpha

Annapolis Junction, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 6 days ago

Job description

A little about us:
 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:

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.

This role is hands-on across all areas as a data scientist; from understanding customer requirements and collecting data, to developing visualizations and advanced analytics to make data-driven recommendations and decisions. You will work directly with intel analysts to develop prototypes and novel solutions that satisfy complex operational needs. 
  
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:     

  • Large dataset experience
  • Strong familiarity with data science applications such as association analysis, graph/network analytics, clustering, text analytics, classification and regression (multivariate and logistic).
  • Training in the design and implementation of static and dynamic visualizations in R, Python, Tableau, or similar visualization software.

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 or exposure to Natural Language Processing (NLP).
  • 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 mind with 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 we continue 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 themselves and their dependents in the form of a robust benefits package.  Our total compensation package includes a competitive base salary and benefits such as health, life/disability, 401k, paid time off, professional development, and generous bonus programs.  Please visit our benefits tab 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 sooner than 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 we bring digital transformation to the fight!