About Christopher
Company Page: parestudio.dev
LinkedIn: linkedin.com/in/christopher-collins-029731125
My work sits between AI engineering, data science and software delivery. I build LLM agent workflows, internal automation tools, predictive models, data pipelines, APIs and cloud-based systems that solve real business problems — not demos that never make it into production.
Typical projects include:
- AI agents for research, operations, customer support and internal knowledge work
- LLM workflows using Claude, ChatGPT, MCP, RAG and custom tool integrations
- Data science models for pricing, forecasting, churn, customer lifetime value and optimisation
- Productionising machine learning models into APIs, services and dashboards
- AWS/Docker deployment, backend integration and data infrastructure
I am particularly suited to businesses that need one senior technical person who can understand the problem, design the solution, build the system and explain the trade-offs clearly.
My last role was Head of Data Science at Shift, a London logistics startup. There I delivered a machine-learning pricing framework that increased margin by 20%, and built an AI-powered vehicle routing engine that allowed the business to scale operations without growing the operations team at the same rate.
Alongside client work, I build AI agent products and data-driven applications, including Political Passport, an AI-powered app for helping people understand their political opinions.
Key technologies: Python, LLMs, Claude, ChatGPT, MCP, AWS, Docker, FastAPI, MongoDB, SQL, XGBoost, TensorFlow, GitHub
Key services: AI Engineering, LLM Agents, Data Science, Machine Learning, Workflow Automation, Data Engineering, Cloud Deployment, App Development
English
Native or bilingual
Spanish
Conversational
Can work on-site
London (up to 50km)
Experience
- Pare StudioTechnical Lead & FounderTECHMay 2025 - Today (1 year and 1 month)London, United KingdomFounder and Technical Lead at Pare Studio, an technology studio building practical automation systems for small businesses, startups and lean teams.We design and build AI agents, internal tools and data-driven applications that reduce repetitive work, improve operations and turn messy business processes into reliable software.Typical work includes:- Building LLM agent workflows for research, operations, reporting and internal knowledge work.- Designing AI-powered tools that interact with documents, databases, spreadsheets, APIs and business systems.- Creating automation systems for quotes, enquiries, scheduling, invoicing, reminders and customer communication.- Developing full-stack business applications with frontends, backends, databases and cloud deployment.- Integrating Claude, ChatGPT and other LLMs into real business workflows.- Turning manual spreadsheet or WhatsApp-based processes into structured tools and dashboards.- Helping clients move from vague AI ideas to scoped, buildable and commercially useful products.This role combines AI engineering, software development, product thinking and technical leadership. I work directly with clients to understand the business problem, design the system, build the first version and deploy it into daily use.
- ShiftHead of Data ScienceTRANSPORTATIONNovember 2021 - April 2026 (4 years and 5 months)Led data science and AI engineering from the ground up at a London logistics startup, building production systems across pricing, routing, optimisation and deployment.Key projects:- Built a machine-learning pricing framework that increased margin by 20% with minimal impact on conversion.- Designed and delivered an AI-powered vehicle routing engine using optimisation and constraint programming, allowing the business to scale deliveries without growing the operations team at the same rate.- Built a cloud-based model deployment framework so data science models could be accessed by developers through consistent APIs.- Hired and managed data scientists while continuing to lead technical delivery across deep learning, optimisation and production ML projects.Technologies: Python, AWS, Docker, MongoDB, Optimisation, Machine Learning, APIs
- FSB TechnologyQuantitative DeveloperTECHApril 2021 - November 2021 (7 months)London, UKDeveloping predictive models for different sports markets, which are used to supply prices to the betting markets sold by the business.Frequent implementation of Bayesian probability theory, developing models in Python then rebuilding/deploying in Java.Introduced several new betting markets for football and horse racing.Huge emphasis on efficient coding practices, as prices can be requested multiple times per second on hundreds of different markets, and need to be shown to thousands of customers with minimal latency. Without a doubt this role improved by technical coding skills.
Recommendations
These freelancer profiles also match your criteria
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Education
- BEng Electrical & Electronic EngineeringUniversity of Bath2016Electrical & Electronic Engineering,
- MEng Electrical & Electronic Engineering,University of Bath2017MEng Electrical & Electronic Engineering,
Certifications
- Sequences, Time Series and PredictionCoursera2020
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep LearningCoursera2020