1 to 25 of 86 Remote Permanent SciPy Jobs

Finance London Senior Java Software Engineer (Senior Architecture Programmer Developer Java Python Software Engineer Data Enterprise Engineering Developer Programmer AWS Python Athena Glue Airflow Ignite JavaScript Agile Pandas NumPy SciPy Spark Dremio Snowflake Apache Iceburg Iceberg Arrow DBT gRPC protobuf TypeScript Finance Trading Front Office Investment Banking Asset Manager Financial Services FX Fixed Income Equities Commodities Derivatives Hedge Fund) required … management) Role: Senior Java Software Engineer (Senior Architecture Programmer Developer Java Python Software Engineer Data Enterprise Engineering Developer Programmer AWS Python Athena Glue Airflow Ignite JavaScript Agile Pandas NumPy SciPy Spark Dremio Snowflake Apache Iceburg Iceberg Arrow DBT gRPC protobuf TypeScript Finance Trading Front Office Investment Banking Asset Manager Financial Services FX Fixed Income Equities Commodities Derivatives Hedge Fund Snowflake More ❯

Credit Rates Bonds ABS Vue Angular React Agile AWS GCP Buy Side Asset Manager Investment Management Performance Risk Attribution TypeScript Node Finance Front Office Trading Financial Services Pandas Numpy Scipy) required by our asset management client in London. You will join a team of 4 that is responsible for an in-house built order tracking and communication platform. It will More ❯

Can understand, apply, integrate and deploy Machine Learning capabilities and techniques into other systems. Are familiar with the Python data science stack through exposure to libraries such as Numpy , Scipy , Pandas, Dask , spaCy , NLTK, scikit-learn. Take pride in writing clean, reusable, maintainable and well-tested code. Demonstrate proficiency in automation, system monitoring, and cloud-native applications, with familiarity in More ❯

Degree in Computer Science, Math, Physics, Engineering, or related quantitative field. Minimum of 2+ years of Python developer proficiency with quantitative analysis experience with packages such as numpy, pandas, scipy, scikitlearn, matplotlib, etc. Proficiency in Linux environment (including shell scripting). 1+ years of experience with automation frameworks in software testing (e.g., PyTest, Cucumber). Experience and/or technical More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯

with data visualization tools e.g. PowerBI or Tableau Data extraction and manipulation languages e.g. SQL, Python Knowledge of statistical software and packages such as R, Matlab, Pandas, NumPy or SciPy Experience with algorithmic trading systems and low-latency trading Knowledge of financial markets is desirable but experience of working in other "big data" or HPC environments is equally valid. Hours More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯

preparation of validation reports. What profile are we looking for? Degree in Computer Engineering, Physics, Electronics, Telecommunications or similar. Advanced programming skills in Python, including libraries such as NumPy, SciPy, pandas, Matplotlib, OpenCV, and PyVISA. Ability to develop Python programs that process data from a C++ API and handle real-time data transmission via sockets and export results to formats More ❯

MPI, OpenMP, CUDA, Triton); cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g., versioning, testing, CI/ More ❯

growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo team. … Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Strong quantitative skills and a proven track record of solving complex technical problems using data analysis, machine learning, and optimization techniques. Hands-on experience with cloud environments (e.g., AWS) for deploying data More ❯

growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo team. … Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). A degree in a quantitative field such as mathematics, engineering, computer science, physics or a related discipline. Previous experience in energy modelling, with a specific focus on the GB and/or More ❯

growing forecast offering. Developing our power market and dispatch models to grow and enhance Modo's product offering. We use Python and the standard scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). Working closely with our product and analytics functions to ensure the product we deliver aligns closely with user needs and provides value to the wider Modo team. … Qualifications: 3 to 5 years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.). A degree in a quantitative field such as mathematics, engineering, computer science, physics or a related discipline. Previous experience in energy modelling, with a specific focus on the GB and/or More ❯

Skills Experience working with large geospatial raster and vector datasets, including Earth Observation or climate data. Proficiency with processing large, complex datasets using Python-based geospatial tools (xarray, numpy, scipy, dask, geopandas, OGR, GDAL). Strong quantitative skills with the ability to extract insights from spatial data. Familiarity with modelling concepts from hydrology, atmospheric sciences, or environmental sciences. Desirable Skills More ❯

Qualifications: Advanced Python skills with experience in backend frameworks like Flask , FastAPI , or Django . Ability to write efficient, reusable, and scalable code. Experience with libraries like NumPy , Pandas , SciPy , or any others commonly used in data processing or modelling. Strong understanding of data structures , algorithms , and complexity analysis . Mathematical or Computational Modelling: Experience with implementing mathematical models in More ❯

and statistics (probability distributions, probability, bayesian stats etc.) Good working knowledge of Python Implementing end-to-end ML pipelines Hand-on experience in Python data science ecosystem (e.g. numpy, scipy, pandas, scikit-learn, matplotlib etc.) Deep Learning frameworks (TensorFlow, PyTorch, MLX) Popular classification and regression techniques Unsupervised learning & matrix factorisation algorithms Natural Language Processing (NLP) and document processing Generative AI More ❯