John Nnamchi, Developer in Montreal, QC, Canada
John is available for hire
Hire John

John Nnamchi

Verified Expert  in Engineering

Bio

John is an experienced developer specializing in data visualization platforms and high-frequency-low-latency data processing systems. His pedigree includes building analytics dashboards at Microsoft, developing a real-time ad exchange platform that processes 5+ billion auctions a day at Index Exchange, and contracting independent projects for corporations. Since 2021, John has been at Bloomberg, developing BQuant, Bloomberg's data visualization and quantitative investment workflow platform.

Portfolio

Bloomberg
Python, Django, React, Full-stack, Data Analytics, OpenAI, Go...
SIMVO
Vue, Node.js, Chart.js, Wix, Facebook Ads Manager...
Index Exchange
Go, Perl, Apache, NGINX, MySQL, Aerospike, Low-latency Software...

Experience

Availability

Part-time

Preferred Environment

Vue, Python, JavaScript, Go, Flask, MongoDB, Chart.js, Data Analytics, Data Visualization, React

The most amazing...

...data visualization tool I've developed is valuencer.io. The tool has unique charts with drag interactions used by L'Oréal Canada to price their influencers.

Work Experience

Senior Software Engineer

2021 - PRESENT
Bloomberg
  • Developed the BQuant Instrumentation/telemetry pipeline that provides real-time usage patterns. Produced a standardized message format across BQuant contexts and common session ID to track users across various BQuant platforms they use.
  • Contributed to a project workflow. Developed a React modal enabling BQuant users to search for people to send projects to. Built numerous Python API routes to resolve user details by partial name, UUID, and community ID and execute the project sending.
  • Embedded Bloomberg auth state into BQuant sessions and refined the back-end auth server to handle custom redirect and cookie allocation workflows, allowing users to access any external, protected Bloomberg resources without needing to log in again.
  • Oversaw the Agile Methodology practices of my 5-member team. I led sprint planning, backlog grooming, and retros. My iterative process has improved work estimation accuracy and productivity (the story point completion rate) by 30%.
Technologies: Python, Django, React, Full-stack, Data Analytics, OpenAI, Go, Data Visualization, CI/CD Pipelines, Docker, APIs, TypeScript, Amazon Web Services (AWS), Git, Front-end Development, Material UI, Web Frameworks, CSS, Kubernetes, Google Cloud Platform (GCP), Terraform, Auth0, Front-end, HTML5, CSV, CSV File Processing

Founder

2018 - PRESENT
SIMVO
  • Built various full-stack software services and created educational content production for multiple clients ranging from corporations and university students to individuals with total billing exceeding $20,000.
  • Developed an Instagram influencer pricing tool called valuencer.io with a Vue front end and Python Flask back end for L'Oréal Canada.
  • Created a dashboard of interactive charts for valuencer.io to present historical post engagements (likes and comments) and a data drag-and-drop feature to help users pinpoint an ideal future post-engagement target and determine the associated price.
  • Redesigned ResearchFDI's (researchfdi.com) platform using HTML, CSS, JavaScript, and Bootstrap to build a data analytics platform consumed by their clients and internal employees, netting $100,000 per year for FDI.
  • Founded Simplify McGill, an organization helping students navigate life in Montreal through articles, media posts, and events. Managed 12 individuals split into content and marketing teams that coordinate the production and promotion of our material.
  • Led Simplify McGill. Its website simplifymcgill.com achieved traffic of over 400 monthly readers and Facebook and Instagram communities' reach of over 4,000 likes and followers.
  • Built a web app, SIMVO Degree Planner, that helped over 1,000 McGill students plan and manage their academic degrees while I was at McGill. Received $15,000 and the Scarlet Key, McGill's most prestigious award for extracurricular activities.
  • Recorded an online software programming course for SIMVO Education and taught it to university students, working professionals, and a cohort in Nigeria. My latest student acquired a new job as a configuration engineer with a 22,000 salary increase.
Technologies: Vue, Node.js, Chart.js, Wix, Advertising Tools & Platforms, Facebook Ads Manager, Zoho CRM, Cloud Firestore, Next.js, Large Language Models (LLMs), MongoDB, Data Visualization, APIs, Amazon Web Services (AWS), Git, Front-end Development, Azure, Material UI, Web Frameworks, CSS, Google Cloud Platform (GCP), Auth0, Front-end, HTML5, CSV, D3.js, CSV File Processing, Highcharts

Senior Software Engineer

2018 - 2021
Index Exchange
  • Built and deployed high-frequency-low-latency solutions that power real-time advertising auctions to distributed systems on 6,000 Linux servers in 10 DCs worldwide, processing over 50 billion requests and generating more than 1TB a day.
  • Gathered requirements from the product team. Wrote design and testing specs. Executed implementation and testing, including unit, regression, and CI/CD pipeline. Supplied post push verification steps to operational teams using Bash and Apache Kafka.
  • Discovered that advertisers return the highest value bids when given maximum time to respond, minimizing auction latency. Identified various Perl auction setup workflows as optimization targets using code profiling tools.
  • Designed an experimental framework that quickly built and deployed new experimental releases, paired with a real-time data pipeline using Kafka, InfluxDB, and Grafana, to analyze optimization outcomes, such as advertiser bid response rates and spend.
  • Relied on Grafana analytics dashboard to provide feedback on MVP release performance. After MVP3 was deployed, the setup latency dropped by 40ms (25%), translating to a $110 thousand per day ad spending increase.
  • Built a Python Kafka consumer analyzing auction dynamics and bidding behavior. Designed a statistical algorithm that produced a competitive index (CI) based on a winning bid against the distribution of other bids.
  • Used CI to maximize bidder price reduction without letting them loose in the downstream auction. Reduced the mean price per ad and led to over 10% savings for advertisers.
Technologies: Go, Perl, Apache, NGINX, MySQL, Aerospike, Low-latency Software, Agile Software Development, Ansible, CI/CD Pipelines, Kafka Streams, Node.js, Angular, Amazon EC2, Data Visualization, Docker, APIs, Amazon Web Services (AWS), Git, Front-end Development, Web Frameworks, CSS, Kubernetes, Google Cloud Platform (GCP), Auth0, Front-end, HTML5, CSV, CSV File Processing

Associate

2017 - 2018
Microsoft
  • Supported the Microsoft federal sales office with weekly sales reports and dashboards, helping them reach the goal of streamlining the Government of Canada's digital transformation and attaining an FY18 quota of over $120 million.
  • Managed and enhanced a Power BI dashboard used for our weekly tech-sales cycle management, which enabled the team’s coordination on quota attainment, opportunity tracking, and identification of crucial enablers in deals.
  • Initiated the development of Azure consumed revenue (ACR) projection reports that all account managers used for FY18 territory presentations presented to global sales directors.
  • Built a program that drafted a word contract based on an Excel purchase order. Deployed it to Microsoft's software reseller, reducing contract writing time by 95% and drafting $80+ million worth of enterprise contracts with the Government of Canada.
Technologies: SQL, Microsoft Power BI, Excel VBA, C#.NET, Data Analytics, Data Visualization, Azure

Valuence: Influencer Pricing Tool

https://valuence.io
The entire application of this Instagram influencer pricing tool that I built. The app is with the Vue front end and Python Flask's back end. The unique value proposition comes from the state-of-the-art analytical views provided by the platform, including:

• A visually appealing dashboard of interactive charts presenting influencers' historical post engagements, such as likes and comments.
• A chart data point dragging feature helping marketers pinpoint an ideal future post engagement target and determine the associated price.
• A dragging feature updating all other charts in real time to maintain consistency with a desired new post's date and time and allow easy engagement comparison to previous posts.
• Pricing also updates in real-time on drag, allowing immediate determination of the correct price to charge based on estimated engagement performance.

L'Oréal Canada is currently using this tool in Montreal, saving over 40% of the marketing budget on the analyzed influencers.

ResearchFDI | FDI 365 Platform

https://researchfdi.com
ResearchFDI is a corporation specializing in providing opportunities for organizations looking to invest in economic development initiatives. I redesigned their client-facing data analytics platform.

The visualization layer of their data was managed in the Zoho CRM platform. The platform allowed users to search for a company meeting specific investment criteria and see detailed views of said companies with charts, graphs, and numerical calculations representing key company factors. There were additional views, such as an article vault, to view historical data on older companies in the system.

I used HTML, CSS, JavaScript, and Bootstrap to enable the data visualization capability consumed by FDI's clients and internal employees. This product nets over $200,000 per year for ResearchFDI.

Simplify McGill

Simplify McGill is an organization helping McGill University students navigate the resources around McGill and Montreal through a website and social media platform and maximize their university experience.

I oversaw 12 individuals split into a content team that continuously produces articles, videos, and other media and a marketing team that promotes the created content.

The website simplifymcgill.com has over 400 monthly readers and its Facebook and Instagram communities have over 4,000 likes and followers.

KAJ Medical

https://kajmedical.com/
KAJ Medical is a multinational company providing various services within the medical supply chain industry. They were looking to digitize numerous inefficient processes within the space, notably, the ability to verify the legitimacy of potential purchasers and manufacturers claiming to be interested in a purchasing deal.

SIMVO was tasked to oversee the development of the eKYC branch of KAJ's trade financing platform, which automated the due diligence process of applicants. We implemented applicant company email and website domain verification, user background and credit check, and an AI photo-recognition-based document tampering detection system to verify the validity of supporting documents.

KAJ Medical currently has revenues exceeding $5 million per year, and demos of the eKYC product have helped them raise an additional $1 million in funding.
2014 - 2017

Bachelor's Degree in Biochemistry

McGill University - Montreal, Canada

NOVEMBER 2017 - PRESENT

Machine Learning

Coursera

Libraries/APIs

Chart.js, React, Vue, Node.js, REST APIs, OpenCV, D3.js, Highcharts

Tools

Microsoft Power BI, Kafka Streams, Git, Auth0, Apache, NGINX, Ansible, Wix, Facebook Ads Manager, Advertising Tools & Platforms, Terraform

Languages

HTML5, Python, JavaScript, Go, HTML, CSS, TypeScript, CSS3, TypeScript 3, SQL, Excel VBA, C#.NET, R, Octave, Perl, C#

Frameworks

Angular, Django, Flask, Next.js, Material UI, Web Frameworks, Bootstrap, .NET

Platforms

Amazon EC2, Amazon Web Services (AWS), Firebase, Docker, Kubernetes, Google Cloud Platform (GCP), Zoho CRM, Azure

Paradigms

Unit Testing, UI Design, Anomaly Detection, Agile Software Development, Management, Agile

Storage

MongoDB, MySQL, Cloud Firestore, Aerospike

Other

Data Analytics, Data Visualization, Full-stack, Front-end Development, Front-end, Machine Learning, Low-latency Software, CI/CD Pipelines, Web Scraping, Data Scraping, APIs, CSV, CSV File Processing, Analytical Thinking, Critical Thinking, Complex Reasoning, Linear Regression, Logistic Regression, Neural Networks, Support Vector Machines (SVM), Unsupervised Learning, Recommendation Systems, OCR, Deluge, Leadership, IT Management, SEO Marketing, Large Language Models (LLMs), OpenAI, Image Recognition

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring