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Entry Level Data Science Jobs in Philadelphia, TN

Dairiconcepts, L.P.

Lab Technician

Knoxville, TN

$18.72 - $22/hr

General Purpose: This is the entry-level, non-certified laboratory technician position for ... analytical data meets the highest standards for accuracy and precision. Job Duties and ...

Guida's Dairy

Lab Technician

Knoxville, TN

$18.72 - $22/hr

General Purpose: This is the entry-level, non-certified laboratory technician position for ... analytical data meets the highest standards for accuracy and precision. Job Duties and ...

All JobsData Science JobsEntry Level Data Science JobsEntry Level Data Science Jobs in Philadelphia, TN

Entry Level Data Science information

See Philadelphia, TN salary details

$9

$16

$23

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 Philadelphia, TN is $16.84, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $18.89 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 cities near Philadelphia, TN are hiring for Entry Level Data Science jobs? Cities near Philadelphia, TN 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 Philadelphia, TN as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $35,017 per year, or $16.8 per hour.
Analytics Engineer I (Entry-Level) (3897)

Analytics Engineer I (Entry-Level) (3897)

Navarro Inc.

Oak Ridge, TN • On-site

Full-time

Posted 20 days ago

Job description

Navarro Research and Engineering is recruiting anAnalyticsEngineerI(Entry-Level)(3897)in Oak Ridge, TN.

Navarro Research & Engineering is an award-winning federal contractor dedicated to partnering with clients to advance clean energy and deliver effective solutions for complex challenges in the nuclear and environmental fields. Joining Navarro means being a part of an exceptional team committed to quality and safety while also looking for innovative strategies to create value for the client's success. Headquartered in Oak Ridge, Tennessee, Navarro has active programs in place across the nation for DOE/NNSA, NASA, and the Department of Defense.

Position Summary

The Analytics Engineer I (Entry-Level) will support Navarro's Data & Analytics team by helping build andmaintaindata pipelines,assistingwith reporting and dashboarding efforts, and contributing to applied AI projects. This role is well suited for an early-career professional interested in growing intoa strong analyticsor applied AI contributor, including work involving AI/ML techniques to extract, structure, andvalidatekey information from unstructured documents.

Responsibilities

  • Assistin designing, building, and maintaining data pipelines and ETL/ELT processes.
  • Write andoptimizeSQL queries to extract, transform, and analyze data from multiple sources.
  • Support the development of dashboards and reports using Excel and other business intelligence tools.
  • Use Python and/or R to automate data workflows, clean datasets, and perform exploratory analysis.
  • Build and support AI/ML-driven workflows for extracting key text and structured data from documents, including NLP, LLM-based extraction, and OCR plus ML pipelines.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data and applied AI project needs.
  • Help document data models, pipeline logic, and AI/ML workflow processes.
  • Contribute todata quality checks and validation processes for both traditional data and AI-generated outputs.

Apply