22 of 22 NumPy Jobs in London

machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science or machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Solid understanding of software engineering principles, including object-oriented programming, data structures, algorithms, and design patterns. Ability to quickly learn ...

Java, SQL, Shell Scripting, Node.js, Streamlit IDE experience: PyCharm, VS Code, JupyterLab, Eclipse, Notepad++, Sagemaker Studio, Azure ML Studio, Vertex AI Workbench Python Libraries NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras, PyTorch, PySpark, SpaCy, SciPy, NLTK, Statsmodels, Boto3, AzureSDK NLP & LLMs BERT, Word2Vec, Universal Sentence Encoder, NLTK, embeddings, fuzzy matching ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

entity resolution. GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

your Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using ...

parallelised applications, including memory management. Experience with widely used tools in data science and machine learning. Developers should be somewhat familiar with libraries like NumPy, pandas, scikit-learn, and PyTorch. Proficiency in testing approaches and frameworks like pytest as well as automation tools like Github Actions or Travis ...

models, experiments, and technical processes. Required Skills & Qualifications:- Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras. Experience in Natural Language Processing (NLP) and/or Computer ...

working alongside traders or within a trading floor environment Knowledge of market data feeds and trading workflows Experience with performance optimisation or numerical libraries (NumPy, Pandas, etc.) Seniority Level Assistant Vice President (AVP) Strong mid-level to senior hands-on engineer Confident operating independently in a front-office setting ...

impact GenAI solutions then this could be for you! Were looking for Engineers offering competent core technical skills in Python Programming, Data Handling with NumPy, Pandas, SQL, and use of Git/GitHub for version control. Any experience with these GenAI Use Cases would be relevant and desirable; Chatbots, copilots ...

Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful ...

Experience with recommender systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps ...

methodologies and contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ...

science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile ...

technical discussions, code reviews, and agile delivery Required Skills & Experience Essential 36+ years commercial experience in Applied ML or Data Science Strong Python (pandas, numpy, sklearn or similar) Strong SQL Experience building and iterating on predictive models Conditional (must meet at least 2 of the below) Time-series modelling 2+ ...

3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks ...

experience provided as a guide) Can independently train, evaluate and iterate on models given a clearly defined problem Is comfortable with Python (pandas/numpy/sklearn or similar), strong SQL, and relational databases Can work with imperfect real-world data and optimise for practical impact rather than just model ...

commercial experience in Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/CD pipelines) Clearance requirements ...

certification required - includes broker interaction) You have: ✅ 5-6+ years as Quantitative Developer in hedge fund/systematic trading ✅ Strong Python (in-depth NumPy/Numba expertise essential) ✅ Deep Unix systems knowledge (processes, memory, I/O) ✅ Statistical methods, numerical optimization & equity market microstructure ✅ Degree in Mathematics/Physics ...

Strong analytical & problem-solving skills: Able to decompose messy, real-world problems and craft tailored solutions. Proficient in Python & data science: pandas/Polars, NumPy, scikit-learn, Jupyter, Plotly (or similar) Confident with data cleaning, analysis, transformation, and visualisation. Excellent communication: Advanced written and spoken English; concise, direct, and audience …/Postgres. TypeScript fluency: Able to read TS and collaborate on data contracts with the Command team. Our environment Python, Polars/pandas, NumPy, scikit-learn, Plotly, SQL/Postgres, NVIDIA cuOpt, HERE APIs, AWS (S3, ECS/Lambda, SNS/SQS), Docker, GitHub Actions, TypeScript/Node (Command services ...

StatArb platform. Live since 2021, trading 24/6 globally. Unified graph-based framework (DAG) across research, production, analytics, risk, and P&L. Deep Numpy/Numba work, processing vast historical datasets and real-time tick data. You'll contribute to shared tooling that researchers actually rely on. … lines. What you'll need: 5+ years as a Quant Dev in a systematic hedge fund (StatArb/equities experience ideal) Deep Python expertise (Numpy/Numba) Strong grasp of statistical methods, numerical optimisation, and equity market microstructure Experience with Unix internals and graph-based data processing frameworks What ...