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Entry Level Data Science Jobs in Suwanee, GA (NOW HIRING)

Scientific Games

Data Center Tech II

Alpharetta, GA · On-site

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and ... The team consists of entry level operators, who may progress to become a Data Center Technician ...

Scientific Games

Data Center Tech II

Alpharetta, GA · On-site

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and ... The team consists of entry level operators, who may progress to become a Data Center Technician ...

PrizePicks

Data Engineer

Atlanta, GA · On-site +1

$105K - $140K/yr

This is an entry-level role where you will work on well-defined pipeline and data tasks under ... A bachelor's degree in Computer Science, Mathematics, or a related quantitative field, or ...

Actalent

Entry Level Recruiter/Sales Trainee

Atlanta, GA · On-site

$195K/yr

Building trusted relationships with our network of engineering and sciences consultants under our ... data) * Performance-based incentives * Quarterly bonuses * All-expenses-paid annual trip for top ...

Pwc

Data Engineer - Senior Associate

Atlanta, GA

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Science information

See Suwanee, GA salary details

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

As of Jul 26, 2026, the average hourly pay for entry level data science in Suwanee, GA is $17.73, according to ZipRecruiter salary data. Most workers in this role earn between $15.00 and $19.90 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Entry level data science roles are open to candidates of all ages, including those starting a career at 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, regardless of age.

What are entry level data science jobs?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

How do I become a data scientist with no experience?

To become an entry-level data scientist with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, working on personal projects, and participating in competitions like Kaggle can demonstrate your abilities and help you gain practical experience. Earning relevant certifications and creating a strong portfolio can improve your chances of entering the field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Entry level data scientists often focus on identifying the most impactful variables or tasks to optimize model performance and efficiency.

What types of projects or tasks can I expect to work on as an entry-level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

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

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

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

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Can I get a data scientist job with no experience?

Entry-level data science positions often require some knowledge of programming languages like Python or R, and familiarity with data analysis tools. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve your chances of securing an entry-level role.
What are the most commonly searched types of Data Science jobs in Suwanee, GA? The most popular types of Data Science jobs in Suwanee, GA are:
What job categories do people searching Entry Level Data Science jobs in Suwanee, GA look for? The top searched job categories for Entry Level Data Science jobs in Suwanee, GA are:
What cities near Suwanee, GA are hiring for Entry Level Data Science jobs? Cities near Suwanee, GA with the most Entry Level Data Science job openings:
Entry Level Data Science jobs near you
Infographic showing various Entry Level Data Science job openings in Suwanee, GA as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $36,885 per year, or $17.7 per hour.
Computer Programmer AI and ML

Computer Programmer AI and ML

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Job description

Overview:
Technologies are evolving at a rapid pace, with innovation being driven by advancements in technology itself. Today, information technology is at a crossroads, poised to reach unprecedented levels, as evidenced by substantial investments from large companies amounting to billions of dollars. R2 Technologies is aligning with this change by forming a team dedicated to training professionals from basic to advanced levels.
Do you have a passion for integrating AI and deep learning into the next generation of software development? Do you want to be part of our journey? R2 Technologies is currently seeking motivated, career-oriented, and client-focused Software Engineers specializing in AI and data science. The ideal candidates will have a strong ability to identify and communicate patterns in data and model behavior. In this role, you may collaborate with multiple teams and technologies (machine learning, quality assurance, cloud infrastructure support, user studies) to improve algorithm quality and guide feature development with a data-driven approach, delivering outstanding computer experiences.
Led by Dr. Raju Manthena, CEO of R2 Technologies, we are building a team to provide customers with the most innovative technology services as efficiently as possible. Our core technology prototypes will feature customizable algorithms designed to meet the needs of various industries, including medical, clinical, pharmaceutical, financial, and insurance sectors.
Required Knowledge, Skills and Abilities
  • Ability to lean and write code in SQL, R, or Python for processing large datasets in distributed cloud environments, and learn and adapt in processing and analyzing healthcare data.
  • learn and practice developing, evaluating, and implementing machine learning models.
  • learn and practice in working with clients across disciplines to develop approaches for use in their business core.
  • learn and practice in working in cloud environments .
  • Graduate level understanding of techniques in machine learning, knowledge representation, and artificial intelligence along with a strong understanding of statistics.
  • Knowledge of software development, machine learning, and technology infrastructure
  • Excellent verbal and written communication skills, strong interpersonal skills, along with demonstrated creativity and latitude in problem solving, including the ability to prioritize and execute multiple competing tasks.

Responsibilities include but are not limited to:
  • Research and evaluate emerging AI, data science, and related technologies, such as Generative AI, technical tools and approaches for responsible and trustworthy AI, Quantum, Image Compression and Recall, and Self Supervised Learning.
  • Stay current on published state-of-the-art data science, AI, and analytics methods and applications and seek out opportunities to apply them against client use cases.
  • Develop statistical and advanced analytics models using advanced analytic techniques such as Natural Language Processing, Graph Analytics, Computer Vision, modeling and simulation, Operations Research, anomaly detection, data visualization and metrics creation.
  • Direct and actively contribute to proof-of-concept studies and research prototypes, including creating prototypes to implement data models.
  • Perform knowledge elicitation from client business problems and understanding and convert that to derived algorithms, and lead and guide teams in this knowledge elicitation process.
  • Apply design thinking or other solution-based methods to solve problems consisting of various qualitative activities that support the generation of insightful, human-centered and impactful design solutions.
  • Identify AI challenges in non-AI projects to enhance the capabilities of data scientists by automating repetitive tasks, uncovering patterns, and providing advanced analytics and predictive modeling techniques.
  • Translate technical requirements to agile tasks to prioritize models and data according to the goals and requirements of the client.
  • Perform solution development through white boarding sessions - Algorithmic problems, data manipulation tasks, or other technical challenges related to data science.
  • Communicate findings to diverse technical and non-technical stakeholders, and engage clients to distill complex technical language. Communicate these findings in language and forms appropriate for the full spectrum of technical background and focus, from end users through executive decision makers.
  • Lead and mentor entry-level, mid-level, and senior level practitioners of AI and data science.
  • Shape Internal Research & Development (IRAD) directions in AI, data science, and related scientific areas. Ensure that these directions are aligned with the practice strategy and client needs.
  • Represent ManTech's data and AI practice in the broader community. Example activities include conference participation, formal or information publications, and speaking at client events.

Qualifications:
• Bachelor's degree in computer science, Engineering, or related field. Good to have Master and or Ph.D.
What we offer : The best in the industry -
  1. Medical insurance
  2. Dental
  3. Vision
  4. Life Insurance
  5. 401K with employer contribution
  6. Paid vacation
  7. Immigration sponsorship for those who requires it - (H1 B and Green cord)
  8. Career guidance
  9. Employee referral bonus
  10. Project based - performance allowances.

Skills:
SQL, Spark, and Python,AI,ML

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