26 to 50 of 53 NumPy Jobs in the City of London

next phase of expansion. You'll be 100% hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, 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 integrate AI/ML models More ❯

decisions and contribute to technical roadmap planning Technical Skills: Great SQL skills with experience in complex query optimization Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark) Hands-on experience building and maintaining data ingestion pipelines Proven track record of optimising queries, code, and system performance Experience with open-source data processing frameworks (Apache Spark More ❯

decisions and contribute to technical roadmap planning Technical Skills: Great SQL skills with experience in complex query optimization Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark) Hands-on experience building and maintaining data ingestion pipelines Proven track record of optimising queries, code, and system performance Experience with open-source data processing frameworks (Apache Spark More ❯

experience applying statistics and data 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, cross-functional teams. Please note More ❯

experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication skills More ❯

experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication skills More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

A recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A More ❯

for? PhD (or MSc + equivalent experience) in Computer Science, Data Science, Mathematics, Physics, or Bioinformatics 5+ years post-qualification experience tackling complex technical challenges Expert-level Python programming (NumPy, PyTorch/TensorFlow, SciPy, pandas) Deep expertise in time-series and sequence modelling (RNNs, LSTMs, transformers, attention mechanisms) Strong foundation in probabilistic models (HMMs, Bayesian inference, graphical models) Track record More ❯

deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong leadership in project delivery, architecture, and technical decision-making. 💡Excellent communicator, able to simplify complex ideas for any audience. More ❯

deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering practices – Object Orientated More ❯

production-grade analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/ More ❯

Skills & Experience 5+ years in AI/ML, with at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain More ❯

is not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such More ❯

is not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such More ❯

language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and trade More ❯

language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and trade More ❯

in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based near More ❯

in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based near More ❯

to gain a deep understanding of quant trading while leveraging your technical expertise to drive results. What you'll bring 2+ years professional experience in Python, including use of NumPy and other scientific libraries. A passion for working with data/dataframes and solving data-related challenges. Strong Pandas experience is required. Minimum bachelors degree in a STEM subject at More ❯

to gain a deep understanding of quant trading while leveraging your technical expertise to drive results. What you'll bring 2+ years professional experience in Python, including use of NumPy and other scientific libraries. A passion for working with data/dataframes and solving data-related challenges. Strong Pandas experience is required. Minimum bachelors degree in a STEM subject at More ❯

scale AI applications, and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical More ❯

data science methodologies Your Background 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 such as Keras or PyTorch More ❯

you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python and experience with frameworks such as PyTorch , NumPy , or Scikit-learn 🧩 Understanding of machine learning algorithms, optimisation, and model evaluation 📈 Strong mathematical reasoning and analytical problem-solving skills 🗣 Excellent communication skills and a genuine passion for learning and More ❯

data science methodologies Your Background 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 such as Keras or PyTorch More ❯