76 to 100 of 215 NumPy Jobs in England

professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker and Kubernetes would ...

data scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools : Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

production. You write production-grade code, not just notebooks.Strong Python and SQL (we use Snowflake). Comfortable with the scientific Python stack: Polars, Pandas, NumPy, SciPy, and scikit-learn. Experience developing and evaluating ML models on tabular data — classification or regression tasks where evaluation matters as much as model choice. ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

write production-grade code, not just notebooks. Strong Python and SQL (we use Snowflake). Comfortable with the scientific Python stack: Polars, Pandas, NumPy, SciPy, and scikit-learn. Experience developing and evaluating ML models on tabular data — classification or regression tasks where evaluation matters as much as model choice. Think ...

data and implementing data science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building ...

working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues.Testing discipline with PyTest and a commitment to meaningful ...

Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‐solving. **Technical Expertise & Tools**: Python: Advanced, production‐grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...

/or sequential modelingExcellent communication skills with the ability to communicate concepts clearly and preciselyExperience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure)NICE TO HAVESExperience as a Data Architect or Senior ManagerProven track record ...

sequential modeling Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track ...

scale.Proven ability to translate business problems into measurable analytical outcomes.Experience taking models from development into production environments.Technical SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection.Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.SQL and large ...

experience with data, including querying, aggregation, analysis, and visualization* Strong competencies in Python for data analysis using the python data science libraries (Pandas/NumPy/SciPy/Scikit-learn).* Strong SQL skills for data retrieval, basic analysis, and data cleansing.* Strong knowledge and application of object-oriented design ...

Masters degree in Computer Science, Engineering, Management Information Systems, or related technical field of study. Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.) Familiarity with version control tools (e.g., Git) and software development best practices. Strong problem-solving abilities and an eagerness to learn about financial markets ...

infrastructure, such as: data pre- and post-processing, sampling and curation, ablation studies, evaluation Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES 5+ years experience in data science or related areas 2+ ...

algorithms and infrastructure, such as: data pre- and post-processing, sampling and curation, ablation studies, evaluationExperience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure)NICE TO HAVES5+ years experience in data science or related areas2+ years ...

training of AI/ML solutionsSkills required: • Overall 8+ years of experience.• 5+ Years of strong Python coding skills and python libraries (like NumPy, Pandas etc.)• 3 Years of solid understanding of generative AI models (GANs, VAEs, LLMs) and their underlying principles• Strong experience in using Neo4J, Mongo DB• Experience ...

analysis/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required.Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.).Proven experience developing, refining, and monitoring NLP models.Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

architecture deployed at scale on Kubernetes. The rest of the tech stack includes Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, and Elasticsearch. We put significant emphasis on design patterns, code readability, automated testing, maintainability, and extensibility. As Software Architect ...

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 ...

technical stakeholders. Best practice: Contribute to how the wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive ...

technical stakeholders. Best practice: Contribute to how the wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive ...