Experience 01
AI/ML Engineer · Savantiq Jan 2026 – Present
Building the AI core of an investment intelligence platform (high-level public summary only).
Highlights
- Architected a unified RAG pipeline (Python/Django) powering chat, memo generation, AI summaries, and research pages — replacing fragmented LLM calls with a modular system covering query optimisation, claim-based retrieval, and grounded answer synthesis with inline citation.
- Designed a claim-first retrieval architecture to eliminate context contamination, integrating AWS Bedrock via a new multi-provider AI client (Azure OpenAI + Bedrock), improving answer consistency and reducing hallucination.
- Led migration of a legacy chat entrypoint to a modular SmartRouter → ChatPipeline architecture, eliminating a dual-entrypoint system with a full test and rollout plan.
- Built an LLM evaluation framework capturing router decisions, retrieved context, and user feedback — enabling proactive quality monitoring rather than reactive incident response.
Experience 02
Research Collaborator · Harvard Health System Innovation Lab Nov 2024 – Present
Automated medical research classification at scale.
Highlights
- Built a few-shot LLM classifier (GPT-4o-mini + RF ensemble) that automated classification of a 200,000-record cancer research dataset with 93% human-machine agreement — reducing manual labelling effort by over 80%.
- Designed a precision-first abstention mechanism that eliminated human verification of positive decisions, enabling clinical experts to focus on genuinely ambiguous cases.
- Co-authored: Public and philanthropic research funding, publications, and research networks for cancer in the Commonwealth and globally between 2016 and 2023: a comparative analysis, The Lancet Oncology 26(9), e466–e476, 2025.
- Invited to the Lancet Commissioners meeting to advise on AI's role in global cancer control and research equity.
Experience 03
Research Assistant · University of Southampton Jun 2024 – Present
AI agent evaluation, governance, and participatory design.
Highlights
- Achieved top ranking at the Concordia Contest 2024 with a novel LLM agent architecture for cooperative multi-agent interaction — published at NeurIPS Datasets and Benchmarks Track 2025.
- Researching AI governance, explainability, and public engagement in participatory agentic system design — paper under review at ACM CHI.
- Selected for the Cooperative AI Summer School 2025; developed evaluation metrics for exploitability in multi-agent systems.
Experience 04
Data Science Intern · Stellar Fusion Aug 2023 – Oct 2023
Financial metrics analysis from SEC filings.
Highlights
- Built a Python/SQL pipeline to ingest, clean, and structure financial metrics from SEC filings and MongoDB company data across 500+ company records.
- Automated cross-sector metric comparisons using K-means clustering and TF-IDF NLP — presented as a proof of concept to senior stakeholders.
Experience 05
Data Science Consultant · LSEG May 2022 – Jul 2023
Real-time market monitoring at infrastructure scale.
Highlights
- Led the Operational Readiness Centre project — reduced critical incident detection time by 80% through automated, real-time market health monitoring pipelines (AWS S3, Glue, SageMaker, ElasticSearch, Snowflake, ServiceNow).
- Built end-to-end data pipelines across 5+ source systems, delivering operational insights via PowerBI and Kibana to Capital Markets stakeholders.
- Prototyped a predictive delay-detection model using AWS SageMaker, extending the system from reactive monitoring to proactive incident prevention.
- Developed an LSTM-based email classifier (85% accuracy) reducing mean client response time by 25%.
