Data Science & Analytics Consulting

Turning complex data into strategic insight

Data science and AI, built and tested properly.

I build machine learning systems, NLP pipelines, and analytical tools that help organisations make better decisions. Specialising in financial analytics, risk assessment, and applied AI.

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14+
Years in Technology
Cambridge
Career Accelerator in Data Science, ML & AI (2025)
London
Based in the UK
About

Data science built on industry experience

I spent over 14 years in software testing at Sky, latterly as Test Manager, where I led cross-functional teams, optimised complex technical processes, and delivered a 25% reduction in resource demand through systematic quality engineering.

That experience taught me how large organisations actually work, where data gets lost, where decisions get made on instinct rather than evidence, and where machine learning can genuinely move the needle.

In 2025, I completed the Career Accelerator in Data Science with Machine Learning & AI (Certificate of Completion, University of Cambridge Institute of Continuing Education with FourthRev), formalising the analytical and engineering skills I now apply through RJ Data Voyage. My final employer project, a team prototype for a UK financial regulator, combined NLP sentiment scoring with financial-metrics extraction across public disclosures from systemically important banks.

I work with organisations that need practical, production-ready data solutions rather than slide decks and theory. If the problem involves unstructured text, complex classification, time-series forecasting, or turning messy data into clear strategic insight, I can help.

Industry-Tested Approach
14+ years in software testing and test management at Sky, delivering under real-world constraints with measurable outcomes.
Cambridge-Trained
Career Accelerator in Data Science with Machine Learning & AI, Certificate of Completion, University of Cambridge Institute of Continuing Education with FourthRev (2025). Grounding in ML, NLP and statistical methods.
Full-Stack Data Science
From data preparation and modelling to a documented, working prototype, such as a self-hosted AI system built for a client.
25%
Resource demand reduction at Sky
81
Public bank reports and transcripts analysed (G-SIB team project)
19
Published case studies
14+
Years in technology at Sky
Services

How I can help

Three focused ways I turn data and AI into working systems for organisations in regulated and data-heavy sectors - practical, validated, and built to run.

Data Science & ML
Predictive modelling, segmentation & forecasting
From a first model to production deployment - classification, clustering, forecasting and dashboards for data-heavy teams.
NLP & Text Analytics
Turn unstructured text into insight
Sentiment, topic modelling, entity extraction and summarisation across reports, transcripts and feedback.
Applied AI / RAG
Privacy-first local LLM & RAG
The capability of modern AI without sending your documents to a third-party AI provider - local models, RAG and query engines.
How I work

From first conversation to working system

Every engagement is fixed-scope and outcome-led - no open-ended billing, no black boxes.

  1. Discovery

    Understand the decision

    We start with the decision you need to make, the data you hold, and what a good outcome looks like.

  2. Scope

    A fixed, defined proposal

    Clear deliverables, timeline and success criteria agreed before any build begins.

  3. Build

    Model, validate, iterate

    Hands-on development against your real data, with progress you can see and question at each step.

  4. Handover

    Production-ready

    Documented code and a dashboard or interface your team can actually use - not a slide deck.

Featured Work

Selected projects

Client work and Cambridge coursework. Each case study states the method, the measured result and its limitations.

Financial Regulation / NLP

G-SIB Disclosure Analysis Prototype

81 reports and transcripts 17,292 text chunks scored

Supervisors monitoring systemically important banks rely heavily on long, unstructured disclosures and earnings-call transcripts. Reading them manually is slow and hard to compare across banks and quarters.

Team project for a UK financial regulator: I designed and built the core NLP pipeline scoring sentiment across three G-SIBs
FinBERTVADERGPT-2
View Case Study
Natural Language Processing

Customer Review Topic Modelling and Emotion Analysis

27,585 reviews analysed 2,031 anger-led reviews

A UK wellness centre chain had thousands of free-text reviews across two public platforms and no systematic way to see what was driving negative feedback.

Topic modelling and emotion classification surfaced four main anger drivers: cleanliness, staff, equipment and fees
BERTopicTransformersLLMNLTK
View Case Study
Anomaly Detection / Operations

Ship Engine Anomaly Detection

422 readings flagged (2.16%) IQR rule

Engine sensor data arrives without fault labels, so abnormal readings have to be found without knowing in advance what a fault looks like.

An IQR rule across six sensors flagged 422 readings for review, compared against One-Class SVM and Isolation Forest
IQRIsolation ForestOne-Class SVMPCA
View Case Study
Applied AI / RAG / Privacy

Private Local Documents AI

25+ file formats no third-party AI provider

Organisations handling confidential documents can't hand them to public AI services. They need the capability of a large language model on infrastructure they control.

Client prototype: a self-hosted LLM on a dedicated GPU server with a three-tier query engine and RAG semantic search, handed over with full documentation
Local LLMRAGSemantic SearchGPUPython
View Case Study
All 19 case studies
Expertise

Core competencies

Six areas where I deliver the most value, each backed by project work and production experience.

Machine Learning

Supervised and unsupervised methods including XGBoost, Random Forests, SVM, ensemble techniques, and clustering (K-Means, hierarchical). End-to-end pipeline development.

Natural Language Processing

Transformer-based models (FinBERT, BERT, GPT-2), topic modelling (BERTopic), sentiment analysis, text classification, and domain-specific NLP for financial and customer data.

Forecasting and Time Series

ARIMA/SARIMA, XGBoost, LSTM networks, hybrid models and decomposition techniques. Applied to demand planning and incident forecasting.

Data Visualisation and BI

Interactive dashboards and visual analytics using Matplotlib, Seaborn, Plotly, and Power BI. Clear, decision-ready presentation of complex findings.

Statistical Analysis

Hypothesis testing (parametric and non-parametric), correlation analysis, regression, and model validation.

Anomaly Detection

Isolation Forest, One-Class SVM and statistical rules (IQR) for flagging irregular readings in operational sensor data, with results prioritised for expert review.

"Raquel consistently demonstrated outstanding leadership throughout our final project in the Cambridge University Data Science Program. She distinguished herself by proposing innovative solutions, guiding the team toward consensus, and ensuring decisions were implemented effectively. She combines strong technical expertise with sound judgment, and excels at aligning teams around clear objectives."

S.S. - Business Information Analyst • Cambridge Data Science Career Accelerator cohort
Insights

Notes from the work

Practical notes on applied AI and data science, drawn from real project work.

Applied AI / RAG
Running a private RAG system on confidential documents
How to give your team AI over sensitive documents, with answers grounded in your own files and nothing leaving infrastructure you control.
Contact

Let's work together

I partner with organisations on data science, analytics engineering, and applied ML projects - from a single well-scoped engagement to an ongoing retainer. If you have a complex data challenge, get in touch to discuss how I can help.

Based in London, available for remote and hybrid work across the UK.

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London, United Kingdom