CV

Employment

2023-    , Senior Cyber Platform Engineer, Department for Work and Pensions - Digital, homeworker

Leading the integration of cloud-native data science applications at the Cyber Resilience Centre with a focus on security, automation, and best practices. Leveraging open source and inner source tools to drive organizational productivity and foster a collaborative engineering culture.

• Cloud-Native Application Development: Architect and build cloud-based data science applications using Terraform, Docker, Python, AWS, and GitLab pipelines, focusing on scalability and performance.

  • Build Terraform modules that implements a new ¨multi-user” architecture for our platform. It enables our team to deploy new multi-user container services with seamless user management through our organization-specific Microsoft EntraID applications

  • Refactorate our Flask application for multi-user authentication by implementating an authentication module that verifies user claim signature in the HTTP header sent by the load balancer.

• Security Automation & Best Practices: Lead the improvement of our security posture and the quality of our development processes. Guide the team in adopting these standards.

  • Hardened our python and neo4j Docker Images using Chainguard to reduce attack surfaces, ensuring secure container deployment.

  • Lead the design and implementation of our testing strategy for our platform and support the implementation of app-specific test plans.

  • Support the team in adopting the configuration as code tool GitlabForm for managing GitLab repository settings, ensuring consistency and security across repositories.

  • Implement pre-commit hooks for Terraform and application repositories, which enforce automating code formatting, linting, and static code analysis to enforce high coding standards.

  • Build new inner source Gitlab CI/CD components for static and dynamic code analysis tools, code vulnerability scanners and dependency updates automation which are used in our CI/CD pipelines

• CI/CD Optimization: Lead the rebuild of our CI/CD pipeline and our infrastructure for continuous deployment of secure, versioned container images.

  • Implement automatic version tagging for our application repositories based on the release-please open source project and conventional commit messages, which automatically generates a version release Merge Requests in our app repostitories

  • Rebuild our CI/CD pipeline to automatically trigger gitlab jobs for tagging Docker images with the current release version and pushing them to ECR, when a GitLab tag is created.

  • Rebuild Terraform modules for our platform to support versioned Docker containers, allowing precise control over app versions deployed in our AWS environments.

• Collaboration & Knowledge Sharing: Actively contributed to the team’s knowledge base by sharing best practices and supporting colleagues in adopting secure, efficient development workflows.

  • Led initiatives to knowledge-sharing sessions with the team on cloud-native development and security best practices.

  • Pair programming sessions with junior team members to support them in adopting efficient development workflows

  • Mentor for junior team members and as part of the cross-government mentoring programme `Catapult` which promotes social mobility

2022-2023, Software Engineer, Department for Work and Pensions - Digital, Newcastle

As a software engineer in a cross-functional Agile team, I played a key role in the development and deployment of a prototype cloud-based AI solution designed to extract insights from handwritten letters sent to DWP services. My contributions focused on both AI model optimization and cloud infrastructure deployment, with a strong emphasis on coding standards and best practices.

• AI Model Optimization: Led the development of the AI component by creating a comprehensive test dataset and fine-tuning the labels and thresholds used in our zero-shot classification model, based on the BART-large-MNLI model. This optimization significantly improved the model’s accuracy in identifying relevant categories of vulnerable persons.

• Cloud Infrastructure & Deployment: Build the Infrastructure and AI solution on Amazon SageMaker, utilizing the AWS Cloud Development Kit (CDK) to automate infrastructure provisioning.

• Serverless Architecture Implementation: Developed and deployed serverless services using AWS Lambda with AWS CDK, employing both Python and TypeScript. This approach enhanced the solution’s scalability and reduced operational overhead.

• Python Coding Standards & CI/CD Integration: Spearheaded the implementation of Python coding standards across the team and the organisation, integrating these standards into the CI/CD pipelines.

2021-2022, R&D Software Developer, OSE Engineering, France

Led the development of innovative software prototypes with a focus on both front-end and back-end technologies, and best practices in software development.

• Full-Stack Development: Managed the full-stack development of a web application for controlling a fleet of TwinswHeel delivery robots, using JavaScript (cytoscape.js) and Django.

  • Implemented key functionalities such as mission design, robot control via WebSocket, and remote operation through WebRTC, ensuring high performance and reliability.

• Python Development: Developed a Python package for solving the electric vehicle routing problem, incorporating interactive map visualizations with Folium/Leaflet.js.

  • Created comprehensive documentation and example notebooks to support the package, promoting its use across the organization.

• Best Practices & Developer Advocacy: Initiated and authored an internal guide for Python software development best practices, covering project structure, meaningful code, documentation, testing strategies, and continuous integration.

  • Advocated for and facilitated the adoption of these practices across teams, contributing to a culture of high-quality, maintainable software development.

2019-2021, Research Scientist, National Oceanography Centre, Southampton

Analysis of multiple ocean & atmosphere datasets (structured and unstructured) to characterise the physical processes at work in the North Atlantic Ocean (poleward heat fluxes)

• Identified origins of trends and patterns observed in flux variability (cross-correlation analysis, cluster analysis)
• Developed methods (e.g. Monte Carlo) to reduce uncertainties on heat fluxes
• Trained and led support scientists and PhD student to data processing and data analysis methods using Matlab, Python and Git

2014-2018, Research Project Scientist, Scottish Association for Marine Science, Oban

Characterisation of the variability of North Atlantic circulation from ocean observations

• Planned, executed and led fieldwork (transatlantic research cruises, robotic missions)
• Developed reproducible workflow for the data processing of robotic data with the development of a matlab toolbox.
• Designed new methods to characterise the ocean heat transport from new observations (gridding of irregular datasets, objective mapping, spectral analysis, Monte Carlo)
• Led and published reports and research articles on the data obtained from field programmes

2013–2014, Postdoctoral Associate, LOCEAN, Paris

Characterisation of the spatio-temporal scales relevant for the winter mixing of the ocean

• Identified principal mode of variability of ocean currents using dimension reduction methods.
• Detection of coherent eddy patterns in time-series using wavelett analysis.

2010–2013, PhD Fellow in Ocean Physics, CEFREM, Perpignan

Analysis of multi-platform observations to study of the impact of episodic events (storm and winter mixing) on the ocean circulation and the long-term evolution of its properties

• Data gathering, cleaning and exploration of oceanic profiles (>200k), including quality control procedures (cross-calibration,outliers), metadata collection and descriptive statistics
• Analysed spatio-temporal variability of ocean mixing (covariance and time-series analysis)
• Identified spatial regions with similar seasonal cycle using a k-mean cluster analysis

Certifications

• 2024, GIAC Cloud Security Automation Certification (GCSA)

Education

• 2010–2013, PhD in Ocean Physics, CNRS, Perpignan
• 2008–2010, MSc, Atmospheric and Oceanic Physics, Université Pierre et Marie Curie, Paris
• 2005-2008, BSc, Maths-Physics-Chemistry, Université de Strasbourg

Technologies and Languages

Python Libraries

NumPy, Pandas, Xarray, Matplotlib, Holoviews, scikit-learn, networkx, Django, sphinx, pytest, pip

Technologies

Linux, Terraform, Docker, AWS, ECS, Git, gitlab-CI, AWS CDK, Jupyter, Websocket, WebRTC

Other Languages

TypeScript/JavaScript, Shell, HTML, CSS, MATLAB, Markdown, LATEX, SQL

Analytical Skills

• Statistics: Covariance, Cross-correlation, Confidence intervals, Monte Carlo methods
• Time-series: Spectral & Wavelett analysis, auto-correlation, detection of patterns & trends
• Spatial: Geostatistics, Kriging, Objective Analysis
• Supervised and Unsupervised Learning: Classification, Regression, Clustering

Experience with Python

I mostly use Python as a procedural programming and objected-oriented programming language. I love learning new python patterns and write “pythonic” code. For example, when it is suited, I like using assertions, decorators, args and *kwargs parameters, NamedTuples and Data Classes, ABC Classes, dictionary, list comprehensions, or generator expressions.

When I am writing code, I follow the PEP8 guidelines and software engineering principles from Robert C. Martin’s book Clean Code, such as writing code that explains itself and is easy to read, writing bug repellent code, follow DRY and SOLID principles and working with design patterns.

I am also documenting the project continuously by creating markdown or reST files and writing docstrings for all the main functions, classes and modules developed in the project. Then I use Sphinx to automatically extract docstrings and compiles them into a well-structured and easily readable HTML documentation.

I like to use the Pytest framework for my unit and functional tests.

Personal Skills, learned during my academic career

Leadership

• Responsible for the data acquisition, processing & storage for the UK research program UK-OSNAP
• Supervised and trained MSc and PhD students to data analysis methods in oceanography
• Organiser of the Oceanography and Climate seminars at the National Oceanography Centre

Communication

• Published 27 scientific articles in peer review journals (>700 citations), 7 reports
• Delivered regular presentations in international and national conferences (60 incl. 12 invited)
• Engagement with public and stakeholders on climate change

Teamwork

• Inter-disciplinary and international scientific collaborations with physicists, chemists, biologists, geologists, statisticians from UK, US, Netherlands, France, Germany and China
• Close collaborations with scientists, technicians, IT-experts and mariners. particularly during research cruises

Fieldwork

• 12 oceanographic cruises, 200 days at sea in the North Atlantic and in the Mediterranean. Planned and led fieldwork activities, liaise with mariners, cruise reports redaction
• 9 ocean glider missions (underwater robot) [2014-2018]: piloting, data processing and analysis