1 to 25 of 85 Remote NumPy Jobs

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 More ❯

MSc in a quantitative discipline (such as STEM subject or Economics). Proficiency in Python, with a solid understanding of Python libraries (such as NumPy, pandas, Polars, and scikit-learn) for data manipulation and statistical modeling. A minimum of 5 years experience working with Futures order book market data, with More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

oral English language Desirable Experience developing systems with Kafka and stream processing techniques Experience with Linux and running containers on Kubernetes Experience with pandas, numpy, SciKit, and other analytical packages Experience designing distributed microservice based architectures Strong background in mathematics, statistics, or mechanical engineering Experience with QT Python thick client More ❯

oral English language. Desirable Experience developing systems with Kafka and stream processing techniques. Experience with Linux and running containers on Kubernetes. Experience with pandas, numpy, SciKit, and other analytical packages. Experience designing distributed microservice based architectures. Strong background in mathematics, statistics, or mechanical engineering. Experience with QT Python thick client More ❯

datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity More ❯

datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

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 More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark More ❯

/services and their integration with databases (e.g. Postgres); You are familiar with the key tools of the Python data science stack, e.g. Pandas, Numpy and scikit-learn; Some experience with training and deploying ML models; You enjoy writing elegant, well-tested and maintainable code; You are a team player More ❯

and even have the ability to be client facing! Requirements 5+ years experience with Backend Engineering Strong working knowledge with Python/Pandas/NumPy/ETL pipelines Strong AWS experience (ideally Lambda & Step Functions) Strong ETL Experience Beneficial : Experience or interest in the financial markets Experience in client facing 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 ❯

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 ❯

Cloud and AWS. Bonus points Startup experience Experience with Python web services (e.g. FastAPI, Django). Data engineering experience using PyData stack technologies (e.g. NumPy, Pandas, etc.) Experience building machine learning systems with LLMs, RAGs utilising embeddings. Technology Frontend: Typescript, Next.js, Vercel Backend: Go, Postgres, Encore.dev, Google Cloud Services: GitHub More ❯

experience with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ELT processes and data pipelines with platforms like Airflow, Dagster, or Luigi. What's important More ❯

stakeholders across the business. Requirements: 4+ years of experience in Data Science, with a strong focus on AWS cloud solutions. Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL . Hands-on experience with AWS services (SageMaker, Lambda, Glue, Redshift, Athena, S3). Strong understanding of ML model More ❯

be 100% hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, Typescript, PostgreSQL, NumPy, Pandas What You’ll Be Doing - Designing, building, and maintaining scalable backend systems for AI-driven healthcare solutions. Working closely with the ML engineers to More ❯

be 100% hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, Typescript, PostgreSQL, NumPy, Pandas What You’ll Be Doing - Designing, building, and maintaining scalable backend systems for AI-driven healthcare solutions. Working closely with the ML engineers to More ❯

experience in developing and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms More ❯

experience in developing and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms 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 ❯