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Python Notebook Jupyter Jobs in New York (NOW HIRING)

JP Morgan Chase

Applied AI/ML Senior Associate

Manhattan, NY · On-site

$65K - $65K/yr

Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required. * Proficient in Python with hands-on experience in Machine learning and Deep learning ...

Fairygodboss

Lead Data Scientist

Roseland, NJ · On-site

$120 - $150/hr

Work Experience * 2+ years with Databricks or AWS Spark and SageMaker, Python and Jupyter Notebooks. * Build and deploy NLU/NLP models and scalable micro‑services (Flask). * Statistical and ...

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Python Notebook Jupyter information

What is a Python Notebook Jupyter?

Python Notebook Jupyter, commonly referred to as Jupyter Notebooks, are interactive web-based tools that allow users to write and execute Python code in a segmented, cell-based format. They are widely used for data analysis, machine learning, and visualization, providing an intuitive way to mix code, visualizations, and narrative text. Jupyter Notebooks are popular among researchers, data scientists, and educators for their flexibility and ease of sharing results. Additionally, they support multiple programming languages with the appropriate kernels, though Python is the most commonly used.

What are the key skills and qualifications needed to thrive as a Jupyter Notebook developer?

To thrive as a Jupyter Notebook Developer, you need strong proficiency in Python programming, data analysis, and a solid understanding of computational notebooks. Familiarity with Jupyter Notebook, data visualization libraries (such as Matplotlib, Seaborn), and tools like pandas and NumPy is typically required. Excellent communication, problem-solving skills, and attention to detail help convey complex ideas and collaborate effectively with team members. These skills enable efficient, reproducible, and collaborative data analysis workflows essential for research and data-driven decision-making.

How does a Python Notebook Jupyter developer typically collaborate with data scientists and other team members on projects?

As a Python Notebook Jupyter developer, collaboration with data scientists, analysts, and other stakeholders is a key aspect of the role. Developers often work in cross-functional teams, using Jupyter Notebooks to create, document, and share code, analyses, and visualizations in an interactive format. Effective communication is essential, as you may need to explain your code, help troubleshoot issues, or integrate feedback from peers. Version control tools like Git are commonly used to manage contributions and ensure smooth collaboration across the team.

What is the difference between Python Notebook Jupyter vs Data Analyst?

AspectPython Notebook JupyterData Analyst
CredentialsBasic programming knowledge, Python skillsDegree in statistics, data science, or related field
Work EnvironmentData science teams, research labs, tech companiesBusiness environments, consulting firms, finance, marketing
UsageData exploration, visualization, prototypingData cleaning, analysis, reporting

Python Notebook Jupyter is a tool primarily used for coding, data exploration, and visualization, often by data scientists and researchers. Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While both roles work with data, Jupyter notebooks are a technical tool used by data analysts as well, but the roles differ in scope and focus.

What are popular job titles related to Python Notebook Jupyter jobs in New York?

For Python Notebook Jupyter jobs in New York, the most frequently searched job titles are:

What job categories do people searching Python Notebook Jupyter jobs in New York look for?

The top searched job categories for Python Notebook Jupyter jobs in New York are:

What cities in New York are hiring for Python Notebook Jupyter jobs?

Cities in New York with the most Python Notebook Jupyter job openings:

Python Notebook Jupyter jobs near you
Infographic showing various Python Notebook Jupyter job openings in New York as of August 2026, with employment types broken down into 1% Internship, 93% Full Time, 2% Part Time, and 4% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution.

Risk Management Developer / Data Analytics

RedStream Technology

New York, NY

$150K - $165K/yr

Full-time

Posted 5 days ago

Job description

Job Description Risk Management Developer/ Data Analytics NYC/ Onsite Perm Role The Risk Management Group is seeking a developer/data analytics engineer to provide daily support to the team regarding risk analysis/monitoring, and to maintain and extend an existing risk analytics platform supporting structured credit, loan portfolio analysis, and related investment decision-making. The role involves developing tools for valuation, scenario analysis, Monte Carlo simulations, data processing and analysis, model execution, reporting, and visualization. The candidate should be comfortable working with quantitative risk concepts and collaborating directly with business users, but is not expected to design financial models.

Responsibilities: Maintain and enhance existing risk analytics applications and workflows. Support large-scale scenario and Monte Carlo analysis. Develop tools for model execution, data collection, validation, and analysis.

Build and improve applications for default analysis, rating transition matrices, prepayments analysis, regression analysis, and probability/exceedance curve reporting. Work with loan-level and transaction-level time series data from raw source formats through normalized datasets. Improve performance, reliability, logging, auditability, and usability of analytical processes.

Collaborate with Risk Management and IT teams to deliver practical tools for research, valuation, and portfolio analysis. Qualifications: Bachelor's or master's degree in computer science, mathematics, statistics, engineering, data science, financial engineering, quantitative finance, or a related technical field. Strong Python development skills.

Experience with data analysis libraries such as Pandas and/or Polars. Experience with SQL and relational databases, preferably MySQL. Experience automating analytical workflows, including Excel-based processes.

Experience with performance optimization, multiprocessing, parallel processing, or job orchestration. Ability to take ownership of an existing codebase and extend it in a reliable, maintainable way. Working knowledge of quantitative concepts such as Monte Carlo simulation, probability distributions, regression analysis, percentiles, default rates, and transition matrices.

Preferred Qualifications: Experience developing financial, risk, investment, or analytics applications. Experience with FastAPI or similar Python web frameworks. Experience with React and charting libraries such as Apache ECharts or Recharts.

Experience with Docker or containerized deployment. Familiarity with Excel/VBA integration, Jupyter notebooks, PyTorch is a plus where relevant. Familiarity with structured credit transactions, securitization, consumer/corporate loan data is a plus.

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