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Entry Level Python Data Science Jobs in Shreveport, LA

Danaher

Digital Analyst Internships

Shreveport, LA · On-site

$79K - $94K/yr

... Computer Science, Information Systems, or a related field * Familiarity with data analysis ... Basic programming or scripting experience in Python, SQL, or JavaScript * Experience with Sitecore ...

micro1 AI

Bioinformatics Software Engineer

Shreveport, LA · Remote

$80 - $110/hr

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

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Entry Level Python Data Science information

See Shreveport, LA salary details

$13

$58

$85

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

As of Aug 18, 2026, the average hourly pay for entry level python data science in Shreveport, LA is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an entry level Python data scientist?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What are some common challenges faced by entry level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

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

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

What are the most commonly searched types of Python Data Science jobs in Shreveport, LA?

The most popular types of Python Data Science jobs in Shreveport, LA are:

What job categories do people searching Entry Level Python Data Science jobs in Shreveport, LA look for?

The top searched job categories for Entry Level Python Data Science jobs in Shreveport, LA are:

Entry Level Python Data Science jobs near you
Infographic showing various Entry Level Python Data Science job openings in Shreveport, LA as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $120,860 per year, or $58.1 per hour.

AI Training Specialist - Life Sciences

micro1 AI

Shreveport, LA • Remote

$90 - $120/hr

Part-time

Posted 21 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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