26 to 50 of 174 Remote NumPy Jobs

and integrity. •3+ years of experience in data engineering, data architecture, or similar roles. •Expert proficiency in Python, including popular data libraries (Pandas, PySpark, NumPy, etc.). •Strong experience with AWS services—specifically S3, Redshift, Glue (Athena a plus). •Solid understanding of applied statistics. •Hands-on experience with large More ❯

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 More ❯

JUnit, etc.). Attributes: Need to Haves: C++ - Strong understanding of multithreading, asynchronous programming, network protocols. Advanced knowledge of Python and related frameworks (FastAPI, NumPy, Pandas, Pydantic) including multithreading and parallel design principles. Understanding of AWS, including knowledge of Cognito, Pinpoint, IoT, MSK and other services. Deep understanding of user More ❯

Looking For: Previous experience at a tier-one bank or large financial organisation is a plus. Extensive proficiency in Python, including libraries such as numpy and scipy. Experience in Market Risk/Trader Risk development is highly advantageous, though not mandatory. Strong knowledge of Rates and Fixed Income products is More ❯

Looking For: Previous experience at a tier-one bank or large financial organisation is a plus. Extensive proficiency in Python, including libraries such as numpy and scipy. Experience in Market Risk/Trader Risk development is highly advantageous, though not mandatory. Strong knowledge of Rates and Fixed Income products is More ❯

platform. What We’re Looking For 2+ years of hands-on experience in Python development (version 3.8 and higher) Strong knowledge of Python packages: numpy, pandas, SQLAlchemy Proficiency in working with databases (SQL/MySQL). Experience with DevOps practices and tools for continuous integration and continuous deployment (CI/ More ❯

retrieval-augmented generation (RAG) systems Knowledge of optimization techniques for reducing LLM latency and computational costs Software Engineering & Architecture Strong Python development skills (pandas, numpy, scikit-learn, PyTorch/TensorFlow) Experience with web frameworks (Streamlit, FastAPI, or Flask) and frontend technologies Database design and optimization (PostgreSQL preferred) for large protein More ❯

priority. Development and maintenance of Continuous Integration (CI) pipelines. Complex deployments on AWS. Docker or comparable containerization technologies. Nice to have experience: Experience using numpy/pandas/torch/etc. Experience with Golang. Our salary range for the role is £70,000 to £130,000, depending on experience and More ❯

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 More ❯

and deployment. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). More ❯

Development (RAD). Messaging/Data Streaming solution (Kafka, RabbitMQ, etc.). Database Admin. Linux exposure. REST API. Good To Have Languages Python: Pandas, Numpy, FastAPI, data manipulation. Web: JS, HTML, CSS, FE framework (React, angular or similar). Ex Scala, Clojure, Groovy or other functional language. This role offers More ❯

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 More ❯

3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit More ❯

3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit More ❯

and retrieval. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). More ❯

3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit More ❯

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 More ❯

CRM systems and finance/savings data (transaction flows, compliance, user segmentation, etc.) Technical Skills: Proficient in Python, SQL, and data science libraries (Pandas, NumPy, Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps More ❯

analysis, and experimental design Experience with marketing mix modeling, incrementality testing, or causal inference Proficiency in Python for data analysis and statistical modeling (pandas, numpy, scipy, statsmodels) Familiarity with machine learning libraries such as scikit-learn Experience with SQL for data extraction and manipulation Demonstrated ability to translate analytical findings More ❯

3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit More ❯

techniques such as data cleaning, normalization, data imputation, feature engineering, and data transformation, as well as experience with tools and technologies such as Pandas, NumPy, and SciPy. Machine Learning: Knowledge of and experience in working with Machine Learning algorithms such as topic models and other natural language processing methods in More ❯

Technical background with good understanding of the underlying physical principles related to battery technology, electric vehicles, EV charging, and the energy sector. Python experience (numpy, streamlit, scipy, pandas, matplotlib, plotly, poetry, GIT, scikit-learn and other scientific libraries) Excellent mathematical, analytical and problem-solving ability Excellent professional communication, reporting and More ❯

in data engineering roles, ideally within financial services Previous experience leading or managing a technical data team Strong proficiency in SQL and Python (Pandas, NumPy, etc.) Experience with Azure and data architecture, including technologies like Databricks and SQL Server Expertise in SSIS, SSRS, and SSAS This is an excellent opportunity More ❯

end, from ideation to deployment. Be on-call for urgent AI model fixes or system failures. Qualifications Proficiency in Python and related libraries (e.g., NumPy, SciPy, pandas) is required. Strong production experience with at least one framework: LangChain, AutoGen, or CrewAI. Deep understanding of agentic systems, autonomous workflows, and LLM More ❯

an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, React.js, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Git, Jenkins and Elasticsearch. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, automated testing More ❯