live production environment. Experience and strong proficiency in programming languages for data science, e.g., SQL, R and Python alongside the ability to use tools and packages such as Alteryx, Jupyter notebook, R Markdown, TensorFlow, Keras, Pytorch etc. Practical expertise in producing reproducible code and pipelines including documentation, governance and assurance frameworks, automation and code review using tools such as Git. More ❯
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 standard vesting More ❯
design and deployment. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services (e.g., AWS, GCP, Azure) for More ❯
storage and retrieval. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services (e.g., AWS, GCP, Azure) for More ❯
AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to interpret data trends, visualize outputs, and debug More ❯
Playwright or similar testing frameworks. REST APIs: Strong understanding of integrating and working with RESTful services. Data Skills: Experience in data wrangling/analysis (e.g., using SQL or Python, Jupyter Notebook). Collaboration: Experience working in an Agile environment (Scrum/Kanban). Problem-Solving: Strong analytical and troubleshooting skills. Desirable Skills Familiarity with state management libraries (MobX, Redux). More ❯
and other Qualtrics products Acquire data from customers (usually sftp or cloud storage APIs) Validate data with exceptional detail orientation (including audio data) Perform data transformations (using Python and Jupyter Notebooks) Load the data via APIs or pre-built Discover connectors Advise our Sales Engineers and customers as needed on the data, integrations, architecture, best practices, etc. Build new AWS More ❯
DevOps Methodologies: experience of working on Agile projects Good understanding of SOA/Microservices based architectures Good understanding of OOP, SOLID principles and software design patterns Knowledge of Python (Jupyter notebooks) Benefits offered Bonus, Pension (9% non-contributory plus additional matched contributions), 4 x Life Assurance, Group Income Protection, Season Ticket Loan, GAYE, BUPA Private Medical, Private GP, Travel Insurance More ❯
London, England, United Kingdom Hybrid / WFH Options
Airbus
driven methods. Design and execute structured threat hunting playbooks based on known TTPs (e.g., MITRE ATT&CK) and emerging threats, enabling consistent, repeatable hunts. Develop code-based playbooks (e.g., Jupyter Notebooks or Python scripts) that integrate threat intelligence, log sources, and detection logic-making them reusable by SOC, IR, and detection engineering teams. Collaborate with detection engineers to convert hunt … tools (e.g., Splunk, ELK), threat intelligence platforms (e.g., MISP, ThreatConnect), and endpoint detection tools (e.g., EDR/XDR). Experience building code-based hunting or automation playbooks (e.g., Python, Jupyter Notebooks, PowerShell ). Familiarity with scripting or automation for IOC enrichment, API integrations , and telemetry analysis. Ability to correlate multiple data sources and pivot across logs, alerts, and CTI for More ❯
