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Python Numpy Pandas Sklearn Jobs (NOW HIRING)

SRP Systems Inc

Senior Python Developer

Princeton, NJ

$127K - $171K/yr

Qualifications 2+ years of experience in Python, Numpy, Pandas Several years of experience in software development and IT SQL and database design experience Additional Information All your ...

SRP Systems Inc

Senior Python Developer

Princeton, NJ · On-site

$127K - $171K/yr

Qualifications 2+ years of experience in Python, Numpy, Pandas Several years of experience in software development and IT SQL and database design experience Additional Information All your ...

PETADATA

Senior Python Developer

Rollingwood, TX · On-site

$117K - $158K/yr

Python (NumPy, Pandas, SciPy) * SQL for data analysis and querying * Linux/Unix environments * Shell scripting for automation * Proven experience in designing and implementing computationally ...

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How much do python numpy pandas sklearn jobs pay per year?

As of Jun 11, 2026, the average yearly pay for python numpy pandas sklearn in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Python Numpy Pandas Sklearn Developer, and why are they important?

To thrive as a Python Numpy Pandas Sklearn Developer, you need a solid understanding of Python programming, data manipulation, and machine learning concepts, usually supported by a degree in computer science, data science, or a related field. Familiarity with version control systems like Git, experience with Jupyter notebooks, and knowledge of scikit-learn, numpy, and pandas libraries are essential technical requirements. Strong analytical thinking, problem-solving ability, and effective communication skills help you interpret data insights and collaborate with team members. These skills and qualifications are crucial for efficiently building, analyzing, and deploying data-driven solutions in real-world projects.

What are 10 careers related to Python?

Careers related to Python include data scientist, data analyst, machine learning engineer, software developer, backend developer, data engineer, research scientist, automation engineer, quantitative analyst, and AI engineer. These roles often require proficiency in libraries like NumPy, Pandas, and scikit-learn, and may involve working in data-driven or software development environments.

How do professionals using Python with NumPy, Pandas, and Scikit-learn typically collaborate within a data science team?

Professionals working with Python, NumPy, Pandas, and Scikit-learn often collaborate closely with data engineers, data analysts, and business stakeholders. They are usually responsible for data preprocessing, exploratory data analysis, and building machine learning models, sharing code and insights through tools like Jupyter Notebooks and version control systems such as Git. Regular communication and code reviews are common practices to ensure accuracy and maintainability of the codebase. Collaboration also involves presenting findings and model results to both technical and non-technical team members, making teamwork and clear communication essential skills for success in this role.

What jobs use NumPy?

Data analyst, data scientist, machine learning engineer, and quantitative analyst roles frequently use NumPy for numerical computations and data manipulation. These jobs often require proficiency in Python, along with skills in Pandas and scikit-learn, to analyze large datasets and develop models efficiently.

What is the difference between Python Numpy Pandas Sklearn vs Data Scientist?

AspectPython Numpy Pandas SklearnData Scientist
Primary FocusData manipulation, analysis, and machine learning model development using Python librariesData analysis, modeling, interpretation, and communicating insights
Required SkillsPython, data libraries (Numpy, Pandas, Sklearn), basic statisticsStatistics, programming, data visualization, domain knowledge
Work EnvironmentData analysis projects, coding, model trainingData exploration, reporting, stakeholder communication
Industry UsageData preprocessing, machine learning pipelinesBusiness insights, predictive modeling, decision support

Python Numpy Pandas Sklearn are essential tools and libraries used by Data Scientists for data manipulation, analysis, and machine learning. While Python libraries focus on technical implementation, Data Scientists combine these skills with domain expertise to interpret data and generate actionable insights.

What are Python Numpy, Pandas, and Sklearn used for?

Python's Numpy, Pandas, and Sklearn are powerful libraries widely used for data analysis and machine learning. Numpy provides support for efficient numerical computations and multi-dimensional arrays. Pandas is used for data manipulation and analysis, especially for tabular data. Sklearn, or scikit-learn, is a library for machine learning that includes tools for data preprocessing, model building, and evaluation. Together, these libraries form the backbone of many data science and machine learning workflows in Python.

What is NumPy Pandas and sklearn?

NumPy, Pandas, and scikit-learn (sklearn) are essential Python libraries used in data analysis and machine learning. NumPy provides support for large multi-dimensional arrays and mathematical functions, Pandas offers data manipulation and analysis tools, and scikit-learn provides algorithms for modeling and predictive analytics. These tools are commonly used by data scientists and machine learning engineers to process data, build models, and perform statistical analysis.

What is the highest paying Python job?

The highest paying Python jobs typically include roles such as Machine Learning Engineer, Data Scientist, and Quantitative Analyst, especially in finance and technology sectors. These positions often require advanced skills in libraries like NumPy, Pandas, and scikit-learn, along with strong programming and analytical expertise, and can offer salaries exceeding $150,000 annually depending on experience and location.
Infographic showing various Python Numpy Pandas Sklearn job openings in the United States as of June 2026, with employment types broken down into 11% Internship, 56% Full Time, and 33% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Machine Learning ML Engineer

Argyle Infotech

Princeton, NJ

Other

Posted 5 days ago

Job description

Machine Learning ML Engineer

Client Location: Princeton, NJ Duration: 6 MONTHS plus Type: Hybrid

Job Description: We need an ML Engineer, who should work from their Princeton office 2-3 days a week in-person starting ASAP. Here is the high level skillset.

  • Design and Manage production pipelines for enterprise scale projects by running necessary ML tests and benchmarks for model validation
  • Fine-tune, retrain and scale existing model deployments
  • Experience with SOTA models related to NLP like Classification, Summarization, Phrase extraction, Table Extraction and OCR
  • Proficiency in Python (Numpy, Pandas, Spacy, Sklearn), AWS (Terraform, CFT, Lambda, Fargate, ECS), SQL, Docker and Django

Apply