6 of 6 Permanent NumPy Jobs in Bristol

client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control More ❯

level experience in data science or a quantitative academic field. Strong programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience More ❯

precise targeting. Behavioral Logic: Develop complex mission logic, tactical decisions, and targeting sequences using Behavior Trees. Prototyping & Simulation: Rapidly prototype, simulate, and validate algorithms using Python and scientific libraries (NumPy, SciPy, Matplotlib). System Integration: Integrate, test, and deploy GNC software on hardware-in-the-loop (HIL) testbeds and flight hardware with PX4 autopilot stack. Performance Analysis: Analyze simulation and More ❯

are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g. More ❯

is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all More ❯

experience in a senior data science or quantitative academic position Strong Python programming skills, with the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised More ❯