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Scipy Jobs (NOW HIRING)

INSPYR Solutions

Data Analyst

Almont, CO · On-site

$70 - $73/hr

Build reusable Python-based analysis pipelines and tooling (e.g., using pandas, numpy, scipy, statsmodels) to standardize experiment analysis and reduce time-to-insight. * Write and optimize SQL to ...

LVIS

Research Scientist

Palo Alto, CA

$120K - $140K/yr

Proficiency in Python and hands-on experience with frameworks such as PyTorch, SciPy, Numpy * Strong understanding of machine learning and deep learning algorithms and their applications in medical ...

LVIS

Research Scientist

Palo Alto, CA · On-site

$120K - $140K/yr

Proficiency in Python and hands-on experience with frameworks such as PyTorch, SciPy, Numpy * Strong understanding of machine learning and deep learning algorithms and their applications in medical ...

INSPYR Solutions

Data Analyst

Orlando, FL · On-site

$70 - $73/hr

Build reusable Python-based analysis pipelines and tooling (e.g., using pandas, numpy, scipy, statsmodels) to standardize experiment analysis and reduce time-to-insight. * Write and optimize SQL to ...

LVIS

Research Scientist

Palo Alto, CA · On-site

$120K - $140K/yr

Proficiency in Python and hands-on experience with frameworks such as PyTorch, SciPy, Numpy * Strong understanding of machine learning and deep learning algorithms and their applications in medical ...

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Scipy information

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How much do scipy jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for scipy in the United States is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $30.77 per hour, depending on experience, location, and employer.

How does a role focused on SciPy typically collaborate with other technical teams in a research or engineering environment?

Professionals working with SciPy often collaborate closely with data scientists, software engineers, and researchers to develop, optimize, and implement scientific computing solutions. They may participate in cross-functional meetings to align on project goals, share code through version control systems, and perform peer reviews to ensure code quality. Open communication and documentation are critical, as SciPy-based workflows frequently integrate with larger data analysis pipelines or machine learning projects. This collaborative environment helps ensure robust, scalable solutions and provides opportunities for ongoing learning from interdisciplinary team members.

What is SciPy and what is it used for?

SciPy is an open-source Python library that is used for scientific and technical computing. It builds on the NumPy library and provides a wide range of modules for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, and many other mathematical tasks. Scientists, engineers, and data analysts commonly use SciPy for data analysis, modeling, and performing complex mathematical computations efficiently. Its extensive documentation and active community make it a popular choice for both research and industry applications.

What are the key skills and qualifications needed to thrive as a SciPy Developer, and why are they important?

To thrive as a SciPy Developer, you need a strong background in Python programming, numerical computing, and a solid understanding of mathematics or scientific domains relevant to your projects. Familiarity with the SciPy library, NumPy, version control systems like Git, and experience with scientific computing environments are typically required. Analytical thinking, problem-solving skills, and effective communication enable developers to work collaboratively and tackle complex scientific problems. These skills ensure the efficient development of robust, reliable scientific software solutions that support research and data analysis needs.

What is the difference between Scipy vs Data Scientist?

AspectScipyData Scientist
Required credentialsTypically requires knowledge of Python, mathematics, and programming skillsRequires degrees in data science, statistics, or related fields; often includes programming and analytical skills
Work environmentUsed mainly in data analysis, scientific computing, and research environmentsWorks across industries, including tech, finance, healthcare, often in collaborative teams
Industry usagePrimarily in scientific research, engineering, and academiaIn business, tech, and analytics sectors for data-driven decision making

While Scipy is a Python library for scientific computing, a Data Scientist applies such tools along with statistical and machine learning techniques to analyze data and generate insights. Scipy is a technical tool, whereas Data Scientist is a role that leverages tools like Scipy to solve real-world problems.

More about Scipy jobs
What cities are hiring for Scipy jobs? Cities with the most Scipy job openings:
What job categories do people searching Scipy jobs look for? The top searched job categories for Scipy jobs are:
Scipy jobs near you
Infographic showing various Scipy job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $54,791 per year, or $26.3 per hour.

Machine Learning Engineer

Root Access Inc

New York, NY • On-site

Full-time

Re-posted 10 days ago

Job description

About the company
Root Access is a frontier electronics company. We are a NYC-based startup funded by top investors. Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning.
Core Responsibilities
  • Architect Physics Foundation Models: Design and train deep learning models.
  • Build the ECAD Data Pipeline: Develop high-performance asset pipelines to convert geometric, discrete, and multi-layer PCB files (ODB++, IPC-2581, STEP, Gerber) into continuous space data.
  • Multi-Modal Architecture Integration: Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic topologies to downstream spatial physics engines.
  • Optimize for Real-Time Execution: Optimize training and inference pipelines on GPU clusters.

Required Technical Skills & Qualifications
  • Education: Master's or Ph.D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML).
  • Deep Learning Frameworks: 4+ years of expert-level experience with PyTorch or JAX.
  • SciML Expertise: Direct, hands-on experience building and training PINNs, FNOs, etc.
  • Mathematical Depth: Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L-BFGS).
  • Data Pipelines: Strong proficiency in manipulating spatial or geometric datasets using Python libraries (NumPy, SciPy, Shapely, Open3D, or custom voxelization matrices).

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