Data · Decisions · Product

Former strategy consultant turned data scientist.

I start with the problem and use context, data and code to build solutions that solve real needs.

Machine Learning LLM / GenAI Agentic Systems Design Thinking Decision Science
Neil Sinclair

01 / Who I Am

Strategy, data & product — where they overlap.

With an MBA and a Masters in Data Science, I've had seven years of consulting and innovation experience — two in strategy, five in data science. I've worked predominantly for some of the largest firms in Africa and Europe, helping them identify and solve their biggest data and decision-related challenges.

Too often, data science produces elegant models that don't speak to real needs. My time as a strategy consultant taught me that context and customers matter more than theory: start with the problem first, test and iterate with the user second, deliver the solution third.

  • 01Design-thinking workshop to surface the real challenges.
  • 02Prioritise problems by impact and ease.
  • 03Build lean: prototype, test with users, adjust.
  • 04Measure results, refine, and scale what works.

02 / Selected Work

My Experience

Optimisation • Business Case Validation

Heat Pump & TES Optimisation

Built a custom heat pump & thermal energy storage optimisation tool for an early stage entrepreneur. Through numerous stages the tool helped guide the development of the initial business case.

Online Tool →

Multi-Agent • RAG • LLM • API

Multi-Agent Sales Assistant

Built a voice-first assistant that routes conversations, gathers info, and generates personalised content. Multiple agents coordinate with each other throughout the process and external APIs, like Salesforce, were integrated.

Promo Video →

Multi-Agent • RAG • LLM • Databricks

Multi-Agent Data Order Creator

I led a team building a RAG-based IoT data gathering tool for analysts. The raw data was preprocessed with LLM-enhanced data augmentation. The user-facing tool consisted of a multi-agent pipeline with query restructuring, RAG, and multi-step response preparation.

In production

04 / Contact

Got an exciting data challenge?

Reach out and let's talk about how context, data and code can solve it.

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