John Critchley — CV

Email: john.job@critchley.biz | Mobile: +44 7887 733029

Location: South Gloucestershire (near Bristol), UK — open to hybrid Bristol/London and remote roles

LinkedIn: linkedin.com/in/john-critchley

Professional Summary

Senior engineer with 20+ years in financial technology supporting production trading platforms and data systems, plus recent postgraduate training in AI and Machine Learning (distinction-level GPA 4.27/4.33).

Technical expertise: Python (6+ years: automation, data processing, APIs, ML), Linux/Unix administration (20+ years), SQL databases (PostgreSQL, MySQL, Oracle), CI/CD, Ansible, Docker. Experience spans platform engineering, DevOps, automation, and data pipelines in high-stakes financial markets environments.

Domain experience: FX derivatives, interest-rate derivatives, institutional crypto trading, market-data platforms at UBS, FXall, trueEX, and Tassat.

Current focus: Seeking roles in DevOps/Platform Engineering, Python Development, Site Reliability Engineering, or transitioning into AI/ML Engineering and Data Science, leveraging operational experience with recent ML training.

Current Status

Available immediately for contract or permanent roles. Currently developing technical projects (automation tools, data pipelines) while seeking next role. References available on request.

Recent Technical Projects (2024–Present)

While job searching, developed practical automation and AI integration projects:

PopIt3 — AI-Powered Job Analysis System

Built end-to-end pipeline processing job alert emails via POP3/OAuth2, routing to specialised processors
Integrated OpenAI GPT-4o API with structured JSON outputs to analyse job descriptions against CV
Implemented scoring algorithm weighing skills match, location, salary, and role fit against personal criteria
Automated HTML report generation and WebDAV deployment for daily job market analysis
Demonstrates: Python, LLM API integration, OAuth2, structured prompt engineering, data processing
Technologies: Python, OpenAI API, GDBM, OAuth2, WebDAV, email processing

gdata-server — FastAPI Database Service

Developing FastAPI-based HTTP server providing REST interface to GDBM databases
Implementing GET/PUT/DELETE/HEAD operations with proper HTTP semantics and error handling
Designing for both local library use and remote HTTP access with transparent abstraction
Demonstrates: Modern Python web frameworks, API design, database abstraction patterns
Technologies: Python, FastAPI, GDBM, REST API design

Education & Certifications

Post Graduate Programme in Artificial Intelligence and Machine Learning: Business Applications — The University of Texas at Austin (Texas Executive Education) / Great Learning, 2023–2024 — GPA 4.27/4.33. Focus: Python for ML, supervised/unsupervised learning, deep learning (neural networks, CNN, RNN, NLP), model evaluation, feature engineering, practical AI implementation for business applications
MSc Artificial Intelligence — Cranfield Institute of Technology (Cranfield University), 1991–1992. Focus: Expert systems, knowledge representation, search algorithms, neural networks (early era)
BSc Computer Science with Physics — King's College London, 1988–1991
ITIL Foundation Certificate in IT Service Management
Sybase Database Server Training

Key Skills

Programming & Scripting

Python (6+ years): automation, data processing, ETL, APIs, machine learning model implementation, Pandas, NumPy, scikit-learn
SQL: PostgreSQL, Oracle, Sybase ASE, MySQL (complex queries, reporting, data analysis, performance tuning)
Shell scripting (bash/ksh), Perl (legacy systems)

Machine Learning & Data Science

Recent training plus projects.

Supervised learning: regression, classification, decision trees, random forests, SVM, ensemble methods
Unsupervised learning: clustering (K-means, hierarchical), dimensionality reduction (PCA)
Deep learning: neural networks, CNNs, RNNs, transfer learning, computer vision basics, NLP fundamentals
Model evaluation: cross-validation, hyperparameter tuning, performance metrics, bias-variance tradeoff
Libraries: scikit-learn, TensorFlow/Keras basics, Pandas, NumPy, Matplotlib, Seaborn
Feature engineering, data preprocessing, exploratory data analysis

Platform & Infrastructure

Linux/Unix: Debian, Ubuntu, RHEL, Solaris, FreeBSD (20+ years administration)
Configuration management: Ansible, Docker, Jinja2 templating
CI/CD: Git, Jenkins, Bamboo, automated pipelines
Monitoring: Prometheus (Java heap metrics via Jolokia), custom scripts, system health dashboards, observability
Cloud: AWS (foundational), interest in Azure/GCP

Domain Knowledge

Trading platforms: FX spot/forwards/swaps, FX derivatives, interest-rate derivatives, institutional crypto
FIX protocol connectivity, broker/venue integrations
Market data feeds, real-time data processing
Production operations: incident response, change management, operational runbooks

Data & Integration

Data pipelines: ingestion, transformation, ETL, reconciliation
Batch processing, data feeds, ad-hoc data loads
API integration, RESTful services
Database administration: backups, performance tuning, disaster recovery

Testing & Quality

Selenium-based UI automation (Python)
Unit testing (PyUnit/pytest)
Test automation frameworks

Ways of Working

Agile/DevOps teams, cross-functional collaboration
Production change management, incident response, post-incident review
Mentoring, documentation, knowledge sharing

Professional Experience

Product Operations Engineer / Python Developer — Tassat (formerly trueDigital Holdings / trueEX group)

August 2021 – January 2024 (Permanent) | Remote from UK (New York-based)

Institutional crypto trading and payments platform.

Automated platform management, monitoring and health checks in Python, improving reliability and reducing manual operational effort. Contributed Java process heap monitoring via Prometheus and Jolokia integration
Built Python tools for post-restart system checkout, data validation, and ad-hoc data loads into trading and payments systems
Developed data processing scripts to handle reconciliation, reporting, and integration between trading systems and payment rails
Migrated scripted operational functionality into Ansible, using Jinja2 templating to separate environment-specific configuration from business logic
Used Docker-based environments and Selenium UI automation to implement automated platform checkout and configuration validation
Supported build-out of new client environments and contributed to designs that supported ~3x client-base growth
Deployed a major platform upgrade to support generating Fedwire payment messages from API “wire” requests, including data transformation, validation, and operational runbooks
Led and mentored colleagues on good practices for automation, CI/CD, monitoring, operational resilience, and data quality
Performed data analysis and reporting using SQL (PostgreSQL) and Python to provide operational insights

Contract Product Operations Engineer — trueEX / trueDigital Holdings

December 2018 – October 2019 | Remote from UK

Provided production and operational support for the same platform during its earlier phases
Extended automation and monitoring scripts, supported deployment and configuration of new environments

Python Developer / Application Support Analyst — trueEX LLC

November 2017 – August 2019 | London / Remote

Electronic trading platform for interest-rate derivatives.

Developed Python-based reporting and analytics tools to process exchange position reports (LCH, CME) and provide insight to business and client-facing teams
Built data processing pipelines to extract, transform, and load trading data for analysis and reporting
Performed data analysis using Python (Pandas) and SQL (PostgreSQL) to identify trends, anomalies, and operational issues
Built and maintained shell and Python scripts for business process automation, platform monitoring and reporting
Automated platform deployments, upgrades and batch processes for the EMEA trading day
Worked with PostgreSQL data stores for integration and reporting, including data quality checks and reconciliation
Produced documentation and mentored junior team members on operational tooling and data pipelines

Trading Floor Support / Data & Automation Specialist — UBS Investment Bank, FX Trading

April 2010 – August 2014 | Zurich, Switzerland

FX derivatives trading systems.

Took technical ownership of FX derivatives and market-data platforms, supporting real-time data ingestion, processing and distribution
Built monitoring and analysis tools to process and visualise real-time trading data, latency metrics, and system performance
Maintained high platform availability (target 99.8%+), with no revenue-impacting incidents during critical trading hours
Enhanced and automated platform start-up and control procedures using Perl and Python, reducing manual steps and start-up times
Managed secure FIX connectivity, SSL certificate configuration and platform upgrades, including regulatory-driven changes and data segregation
Led technical response to production incidents, including root-cause analysis using data analysis techniques and preventative improvements
Developed scripts for data extraction, transformation and reporting to support trading operations and compliance

Application Support Analyst — FXall (FX Alliance LLC)

May 2008 – April 2010 | London, UK

Multi-dealer electronic FX trading platform.

Supported FX trading applications (spot, forwards, swaps) built on Java and Oracle, ensuring availability for institutional clients
Developed Perl-based monitoring and reporting tools, using Oracle and MySQL for trend analysis and performance tracking
Performed data analysis on trading patterns, system performance, and operational metrics
Wrote FIX diagnostic tools in Perl to help analyse and resolve connectivity and messaging issues
Monitored SLAs, managed incidents and coordinated communication with internal and external stakeholders

Engineering Lead Associate — Firewall Engineering, UBS AG

September 2006 – December 2007 | London, UK

Extended and maintained Perl-based tools and web front-ends used to configure and monitor Netscreen firewalls
Investigated configuration issues, worked directly with the vendor on open problems, and supported analysis of new devices

Senior Support Analyst — Equities Trading, UBS AG

February 2005 – August 2006 | Zurich, Switzerland

Supported equities trading platform, real-time market feeds and broker links (including FIX)
Developed Perl scripts to monitor latency in different parts of the system and provided graphical performance views
Analysed system performance data to identify bottlenecks and optimisation opportunities
Maintained production and “prodtest” environments, ensuring changes were properly tested before release

Support Analyst — European Wealth Management, UBS AG

April 2003 – March 2004 | London, UK

Supported nightly data feeds into wealth-management systems (Oracle, DB2, AS/400), ensuring correctness and timely delivery
Optimised overnight batch flows and produced batch analysis charts using Perl tools
Performed data validation and reconciliation checks

Application Support Analyst & Interface Developer (Contract) — Merrill Lynch Investment Managers

August 1998 – March 2004 | UK

Supported and developed interfaces and batch processes for investment-management systems
Used Perl, shell scripting and SQL across Unix and Windows environments for reporting, data movement and operational automation
Built data integration pipelines between multiple systems

Recent Technical Projects (2024–Present)

While job searching, I have maintained and extended my technical skills through practical projects:

PopIt3 — Job Analysis System

Built end-to-end ETL pipeline in Python to process job postings from email, extract structured data, and score opportunities against CV using semantic matching
Implemented GDBM database backend for efficient key-value storage, email parsing with Python email libraries
Integrated OpenAI API for semantic analysis and job-CV matching using embeddings and similarity scoring
Created FastAPI-based reporting interface to query, filter, and analyse job data with JSON responses
Applied data normalisation, validation, and aggregation techniques
Technologies: Python, GDBM, OpenAI API, FastAPI, email processing, data engineering, REST APIs

gdata-server — HTTP API for GDBM

Developed lightweight HTTP API in Python to provide RESTful access to GDBM key-value stores
Implemented GET/PUT/DELETE operations with proper HTTP status codes, error handling, and content negotiation
Designed API schema and endpoints for efficient data access patterns
Containerised with Docker for reproducible deployments, automated deployment with Ansible
Technologies: Python, FastAPI, GDBM, Docker, Ansible, REST API design

Selected Achievements

Automated platform management, monitoring and post-restart checks in Python for an institutional crypto platform, significantly improving reliability and reducing manual effort
Built data processing and analysis pipelines using Python and SQL to provide operational insights and reporting for trading platforms
Designed and implemented Ansible- and Docker-based deployment and configuration processes, reducing deployment errors and downtime by ~90%
Led the operational implementation of a Fedwire payments integration, including data transformation, validation workflows, and robust operational procedures
Improved FX derivatives platform start-up and monitoring at UBS by enhancing Perl and Python control scripts, contributing to 99.8%+ uptime during trading hours
Built Python and Perl tools for performance and latency analysis across several trading platforms, providing data-driven visibility that supported tuning and incident prevention
Completed postgraduate AI/ML training with distinction-level GPA (4.27/4.33), demonstrating ability to rapidly learn new technical domains

Location & Clearance

Location: South Gloucestershire, near Bristol, UK
Security Clearance: None currently held. Open to SC clearance sponsorship for suitable long-term roles, but cannot accept roles requiring active/current clearance.

Travel Flexibility

Daily commute (up to ~1.5hrs): Bristol, Bath, Swindon, Oxford, Cardiff, Birmingham
Weekly hybrid (2–3 days/week, ~2–2.5hrs): London, Reading, Guildford, Southampton
Monthly visits (~3–4hrs by train): Leeds, Sheffield, Manchester, Nottingham
Monthly visits (by air): Edinburgh, Glasgow, and European cities (e.g., Zurich, Amsterdam)
Fully remote: Any location acceptable

Note: Assess location suitability based on the role's on-site requirements. For example, Leeds requiring 5 days/week onsite is unsuitable, but monthly visits are perfectly acceptable.

Technical Experience Notes

Strong production experience

Python (6+ years production)
Linux/Unix administration (20+ years)
PostgreSQL, MySQL, Oracle (production DBA and development)
Ansible, Docker, Git, CI/CD
Data processing, ETL, SQL analysis

Recent training (postgraduate AI/ML programme)

Machine learning algorithms (supervised/unsupervised)
Deep learning (neural networks, CNNs, RNNs)
Python ML libraries (scikit-learn, TensorFlow/Keras basics, Pandas, NumPy)
Model evaluation and feature engineering
No production ML deployment experience yet — seeking opportunity to apply training in real-world ML engineering role

T-SQL / MS SQL Server: Strong T-SQL experience from Sybase ASE administration (production use at UBS, MLIM). T-SQL syntax is highly compatible with MS SQL Server. No recent MS SQL Server administration experience, but T-SQL fundamentals transfer directly.

Technology gaps to be honest about

Kubernetes: Docker/container experience; production Kubernetes experience needed for senior K8s roles
Terraform/CloudFormation: Ansible and scripting background; IaC tools (Terraform/CF) required for Infrastructure-as-Code positions
Azure/GCP: AWS foundational experience; production Azure/GCP experience needed for cloud-focused roles
Windows Server: Some exposure in mixed environments; NOT dedicated Windows Server 2016/2019/2022 administration
MS SQL Server: Strong T-SQL from Sybase ASE; no recent MS SQL Server administration
Production ML deployment: Recent training but not yet production MLOps/model deployment experience