26 to 50 of 643 Permanent NumPy Jobs

a Data Science 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 More ❯

a Data Science 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 More ❯

a Data Science 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 More ❯

communication skills with the ability to collaborate with both technical and non-technical teams This role is 70% hands on, 30% management Technical Expertise Required - Python - proficiency with Pandas, Numpy, SQLAlchemy, FastAPI, and Pydantic MySQL, PostgreSQL, and Redis Hands-on experience with Google Cloud Platform (GCP) services like Pub/Sub, Cloud Run, VMs, Load Balancers, and Cloud Logging. (AWS More ❯

Hands-on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall knowledge of the Software More ❯

building and implementing data science and machine learning solutions to tackle business problems. Comfort with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary More ❯

for interaction with the models Testing and documentation Requirements: Experienced Python developer Experience utilising machine learning libraries such as (in order of importance) TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy Experience with AWS (principally EC2, S3, SageMaker) or Azure/GCP equivalents Some experience of designing, developing and deploying scalable infrastructure (eg Apache Airflow, Luigi or other cluster management More ❯

experience in Python as a 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 Benefits Our salary range for the role is £70,000 to £130,000, depending on experience and interview performance. List of More ❯

and development, and a strong understanding of computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from data in a financial More ❯

experience, with a minimum of a 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, statistical modeling. A minimum of 5 years experience working with Futures order book market data. With strong familiarity in other financial instruments More ❯

of working in hedge fund or alternative investment environment, working directly with investment team on tech delivery is preferrable Understanding of Python, with libraries/frameworks such as Pandas, NumPy, and PySpark. Understanding of distributed computing, with experience using frameworks like Databricks. Experience with Azure or other cloud platforms (AWS) Experience building data pipelines or ETL tools and Orchestration frameworks More ❯

Stay agile and innovative as technology and client needs shift. Role Requirements Technical Skills Substantial experience in data engineering, analytics engineering, or similar roles. Hands-on expertise with Python (Numpy/Pandas) and SQL. Proven experience designing and building robust ETL/ELT pipelines (dbt, Airflow). Strong knowledge of data pipelining, schema design, and cloud platforms (e.g., Snowflake, AWS More ❯

for analyzing and interpreting large 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: Generous equity package, on a More ❯

machine learning (MLOps), using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning Experience in relevant Data Manipulation, Machine Learning and Statistical Analysis coding packages (eg. in Python: NumPy, Scikit-Learn, Pandas, Matplotlib etc.) Strong skills in data exploration, cleansing, modelling and presentation Strong experience in testing data models and Machine Learning Models Strong experience in data presentation and More ❯

NiFi Familiarity 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 More ❯

and frameworks such as RAG, LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. Experience More ❯

a growing organisation. Role Requirements Technical Expertise 4+ years of experience in analytics engineering, data engineering, or similar roles with substantial experience building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong More ❯

Within Risk Engineering we run a mixture of Linux and Windows, and use Python and C# as primary languages, with an emphasis on Python and the Python scientific stack: numpy, scipy, pandas, scikit-learn, etc. We implement the systems that require the highest data throughput in Java. We implement most of our long running services and analytics in C#. We More ❯

Quantitative Developer - Java (Risk Technology) Millennium is a top-tier global hedge fund committed to leveraging innovations in technology and data science to solve complex business problems. The Risk Technology team is seeking a Quantitative Developer who will utilize Java More ❯

exposure to client pricing and flow analysis. At least 5 years of advanced Java development experience, including: Strong understanding of object-oriented programming and design patterns. Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. Experience with SQL and/or time-series databases. Strong Linux skills and experience working in globally distributed environments. Solid understanding of financial … least 5 years of advanced Java development experience, including: Strong understanding of object-oriented programming and design patterns. Proven experience building high-performance, low-latency systems. Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. Experience with SQL and/or time-series databases. Strong Linux skills and experience working in globally distributed environments. Solid understanding of financial … least 5 years of advanced Java development experience, including: * Strong understanding of object-oriented programming and design patterns. * Proven experience building high-performance, low-latency systems. * Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. * Experience with SQL and/or time-series databases. * Strong Linux skills and experience working in globally distributed environments. * Solid understanding of financial More ❯

problems which until recently were considered impossible, or extremely difficult, to solve. Their core systems run on Linux and most code is written in Python, including extensive use of numpy, scipy, pandas, scikit-learn, etc. But they’re also constantly evaluating new technologies, tools and libraries, meaning you can shape the technology landscape and make an impact early on. Requirements … Passion for AI engineering, someone who stays up to date with major advancement in AI tools and models Strong development knowledge of Python Experience of data analysis techniques, plus numpy, scipy, pandas, etc. Solid Linux platforms experience with various scripting languages Proponent of collaborative software engineering techniques and agile methods Degree with high mathematical and computing content – Computer Science, Mathematics More ❯

Responsibilities Design, develop, and deploy machine learning models to solve complex business problems. Collaborate with cross-functional teams to integrate ML models into production systems. Utilize PyTorch, Scikit-learn, NumPy, and Pandas for data analysis and model development. Develop and maintain APIs for model deployment and integration. Fine-tune large language models to enhance performance and accuracy. Apply deep learning … And Skills Formal training or certification on Data engineering concepts and applied experience cProven experience in building and deploying machine learning models. Hands-on experience with PyTorch, Scikit-learn, NumPy, and Pandas. Proficient in Python programming language and building APIs. Solid understanding of statistics and machine learning theory. Experience with deep learning architectures, including LSTMs and Transformers. Experience in fine More ❯

Extensive platform development experience in the Python 3.x ecosystem Strong understanding of the fundaments of software engineering and design Awareness of data science concepts and technologies (Jupyter/Notebooks, numpy, pandas etc.) Financial markets experience preferred DevOps (CI/CD) Experience preferred Computer Science or relevant Engineering degree This is a £550-£600/day PAYE role (c. More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯