Christopher Little
Verified Expert in Engineering
Software Developer
After earning a first-class bachelor’s degree and a top distinction master’s degree in Computer Science from the University of Cambridge in the UK, Christopher went on to build two tech companies from the ground up. In addition to his technical expertise, Christopher uses his ability to quickly learn and understand client needs when managing and developing projects.
Portfolio
Experience
Availability
Preferred Environment
Amazon Web Services (AWS), Git, WebStorm, Visual Studio, Ubuntu
The most amazing...
...thing I have done is to build the UK's first fully-automated mortgage assistant, totally from scratch.
Work Experience
CTO
Axon
- Conducted initial research to validate business and technical concept.
- Planned and developed infrastructure to conduct an Initial Coin Offering (ICO) for the company.
Lead Developer
Lendr Limited
- Developed the UK's first fully automated robo-advice platform for mortgages.
- Quickly developed an understanding of an unfamiliar domain.
- Integrated numerous third-party providers for KYC, property valuation and bank account auditing.
- Implemented a scalable architecture to generate suitable advice for every client, and deployed to AWS.
- Created three different client interfaces to our engine - for borrowers, lenders and mortgage brokers respectively.
Founder/CEO
Manner AI
- Built a cross-platform analytics dashboard to manage chatbot conversations.
- Developed algorithms to test, personalise and optimise automated conversations.
- Deployed machine learning algorithm to Google Cloud Platform to handle millions of latency-sensitive queries.
- Grew the company from scratch and raised initial pre-seed funding.
- Developed commercial relationships with 3 major chatbot development agencies.
Experience
Grapht
https://imgur.com/4UDWSqAMy approach involved using a relational database as an underlying data store, along with a partial graph representing the same data stored in memory. Queries were then analysed and dispatched to either the original database or resolved through the in-memory store. By taking this approach, Grapht was able to avoid the degenerate worst-case performance of both relational and graph databases. This is particularly beneficial for complex queries which involve both row-centric and graph-centric components.
The linked chart shows this performance increase for Grapht compared to both PostgreSQL and Neo4J for one such query. The percentages indicate the proportion of time spent executing the row-centric (Lenvenshtein) and graph-centric (A*) components of the query. I was awarded a top Distinction for this dissertation, and for my Master's degree overall.
Skills
Languages
ECMAScript (ES6), HTML5, SQL, CSS3, CSS, HTML, TypeScript 2, JavaScript, TypeScript, GraphQL, Solidity, Kotlin, Java, Go, Python, Python 3, Bash
Libraries/APIs
React, Node.js
Tools
Amazon Simple Email Service (SES), Mongoose, AWS SDK, AWS IAM, Visual Studio, WebStorm, Git, Oh My Zsh, Zsh
Platforms
AWS Lambda, Ubuntu, Amazon Web Services (AWS), Amazon EC2, Unix, Linux, Google Cloud Platform (GCP), Mailgun
Storage
MySQL, MongoDB, MariaDB, PostgreSQL, Amazon S3 (AWS S3), Amazon DynamoDB
Frameworks
Redux, Relay, Bootstrap
Other
Learning, Ethereum Smart Contracts, Icon Fonts
Education
Master of Engineering (Distinction) Degree in Advanced Computer Science
University of Cambridge - Cambridge, United Kingdom
Bachelor of Arts (First Class) Degree in Computer Science
University of Cambridge - Cambridge, United Kingdom
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