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Python Numpy Pandas Sklearn Jobs (NOW HIRING)

Palnar

Python Developer

$51.50 - $71/hr

NumPy, Pandas, Django/Flask required. * Data analysis and development work. * Someone with CI/CD ... using python. * It's a new application development work and some old application support.

VDart

AI/ML Lead Engineer

Chester, PA

$98K - $130K/yr

... Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow). • Develop LLM-powered applications using frameworks such as OpenAI, LangChain, Hugging Face, or LlamaIndex. • Design and manage data ...

AM Best Company

Data Engineer

Oldwick, NJ · Hybrid

$125K - $150K/yr

Also, comfortable working with Numpy, Pandas, Python collections, etc Must handle API development using REST. Strong working knowledge of FastAPI, with a primary focus on mastering the REST protocol.

Chabez Tech

Machine Learning Engineer

Portland, OR

... Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) Experience with time-series data analysis and anomaly detection Hands-on experience with causal inference methods (e.g., Bayesian networks ...

Programmers.io

Python + ML

Sunnyvale, CA · On-site

$59 - $81.25/hr

... Python and API's. • Excellent expertise in AI/ML Technologies • Excellent expertise ... in Numpy, Pandas, SciPy • Excellent expertise in Tensor Flow, PyTorch • Experience in ...

Chabez Tech

Machine Learning Engineer

Portland, OR · On-site

... Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) • Experience with time-series data analysis and anomaly detection • Hands-on experience with causal inference methods (e.g., Bayesian ...

Chabez Tech

Machine Learning Engineer

Portland, OR

... Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) • Experience with time-series data analysis and anomaly detection • Hands-on experience with causal inference methods (e.g., Bayesian ...

Chabez Tech

Machine Learning Engineer

Portland, OR

... Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) • Experience with time-series data analysis and anomaly detection • Hands-on experience with causal inference methods (e.g., Bayesian ...

Zortech Solutions

Java Developer with Instabase

Columbus, OH

$47.75 - $61.75/hr

Advise and instruct on the ecosystem of open source tools python spacy pandas sklearn etc compatible with Instabase and how customers can use them Skills Mandatory Skills : Instabase Java,HTML/HTML5 ...

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Python Numpy Pandas Sklearn information

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

As of Jun 12, 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.
Senior Lead Agentic AI & Telecom Billing Transformation

Senior Lead Agentic AI & Telecom Billing Transformation

Yochana IT Solutions

Philadelphia, PA

Other

Posted 10 days ago

Job description

Key Responsibilities

Agentic AI Strategy & Program Ownership

Architecture & Solution Design

AI Governance, Risk & Compliance

Leadership & Stakeholder Management

Required Experience & Skills

Experience

5+ years of experience in AI/ML development, with strong Python based solution delivery

Deep domain experience in Telecom BSS & OSS, covering fixed, mobile, IoT, and converged services

Strong experience designing end to end BSS solutions across Sales, Marketing, Product, Finance, and Customer Care

Hands on experience with major telecom B/OSS COTS platforms (Amdocs, Netcracker, Comarch, Ericsson)

Solid understanding of TM Forum standards and processes

Experience with 5G architecture and core concepts, including network slicing and service enablement

Technical Skills

Programming: Python (NumPy, Pandas, Scikit learn, PyTorch, TensorFlow)

Generative AI & Agentic AI: OpenAI, LangChain, Hugging Face Transformers, LlamaIndex

Web & API Development: Flask, FastAPI, or Django

ML Lifecycle: Model training, evaluation, deployment, monitoring, and drift management

Data Engineering: Data ingestion, preprocessing, visualization (SQL, Pandas, Power BI, Streamlit)

Cloud & MLOps: AWS SageMaker, Azure ML, or Google Cloud Platform AI Platform; Git, Docker, CI/CD pipelines

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, or related field

Certification or specialization in AI/ML, Deep Learning, or Generative AI

Apply