FCA · CONTROLLERS & CANCELLATIONS ·
MSC DATA SCIENCE · DISTINCTION ·
OXFORD · ALGORITHMIC TRADING ·
NLP / OCR PIPELINE · PRODUCTION ·
MULTI-FACTOR EQUITY RESEARCH ·
CFA LEVEL 1 · NOV 2026 ·
QUANTGUARD · IN DEVELOPMENT ·
IFoA ACTUARIAL EXAMS · CT1–CB3 ·
FCA · CONTROLLERS & CANCELLATIONS ·
MSC DATA SCIENCE · DISTINCTION ·
OXFORD · ALGORITHMIC TRADING ·
NLP / OCR PIPELINE · PRODUCTION ·
MULTI-FACTOR EQUITY RESEARCH ·
CFA LEVEL 1 · NOV 2026 ·
QUANTGUARD · IN DEVELOPMENT ·
IFoA ACTUARIAL EXAMS · CT1–CB3 ·

Quantitative Data Scientist

Hisho
Rajanathan

Senior Data Analytics Associate at the Financial Conduct Authority, Authorisations Division — Controllers & Cancellations. Independently developing systematic quantitative research in factor investing and portfolio analytics. Targeting a move into quantitative finance research.

View Projects GitHub ↗ LinkedIn ↗
10+
Years in data
4
Regulated firms
2×
Distinction grades
01 · About

Credentials
that compound

I'm a data scientist with a background spanning actuarial science, financial regulation, and applied machine learning. I've built and deployed production-grade analytical systems inside some of the UK's most demanding institutions.

At the FCA's Authorisations Division, Controllers and Cancellations Department, I work on the risk-based assessment and prioritisation of corporate transactions — mergers, acquisitions, and changes in control at regulated firms — using predictive models, automated data pipelines, and NLP-driven document intelligence.

Outside of work, I'm independently developing systematic quantitative research in factor investing and portfolio construction, building toward a long-term goal of contributing to a multi-strategy systematic fund. I'm currently a CFA Level 1 candidate (November 2026).

Hisho Rajanathan
Production Achievement
Designed and deployed an end-to-end NLP & OCR pipeline at the FCA to extract structured data from complex M&A filings, cutting review time from ~2 hours to under 30 minutes per case.
Quantitative Research
Independently built multi-factor equity research across S&P 500 and FTSE 100 universes, covering momentum, value, quality, and low-volatility premia with rigorous subsample and crisis-period attribution.
Actuarial Foundation
IFoA exams CT1, CT2, CT3, CT5, CT7 and CB3 — self-funded — complementing an MSc in Data Science (Distinction) and Oxford's Algorithmic Trading Programme.
02 · Projects

Research &
independent work

01 · Featured
Multi-Factor Equity Premia Study
Systematic Research · Factor Investing · S&P 500 / FTSE 100
Evaluated four published equity factor premia — momentum (UMD), value (HML), quality (RMW), and low-volatility — across a dual-universe dataset. Constructed equal-weight and risk-parity composite portfolios; risk-parity achieved a Sharpe of 0.17 with a diversification ratio of 1.41x. Conducted subsample stability analysis across four decades, rolling Sharpe decomposition, and crisis-period attribution covering the 2009 momentum crash, COVID drawdown, and 2022 rate shock.
Factor Models Risk Parity Python Pandas Momentum Value Quality
02
NLP Sentiment & Equity Signal
NLP · Financial News · Signal Construction
Built an NLP-based sentiment pipeline to extract features from financial news headlines and analyse their relationship with subsequent equity index movements. Constructed a sentiment-driven trading signal and evaluated its behaviour across different market conditions.
NLP Sentiment Python NLTK Signal Research
03
FCA NLP / OCR Pipeline
Production System · RegTech · Document Intelligence
End-to-end production pipeline combining OCR preprocessing with NLP classification to extract structured financial, ownership, and transactional information from complex M&A filings at the FCA. Reduced manual document review from ~2 hours to under 30 minutes per case.
NLP OCR spaCy Python Azure Production
04
quantguard ↗
Python Library · Open Source · In Development
A Python library for quantitative research rigour and strategy validation — currently in active development. Planned modules include regime detection, deflated Sharpe ratio, combinatorial purged cross-validation, signal half-life, IC analysis, and alpha decay diagnostics.
In Development Python Quant Finance Open Source
03 · Experience

Where I've
built things

FEB 2023 — PRESENT
Senior Data Analytics Associate
Financial Conduct Authority — Authorisations Division, Controllers & Cancellations · London, UK
  • Developed predictive and time-series models to support risk-based assessment and prioritisation of corporate transactions — mergers, acquisitions, and changes in control across regulated financial firms
  • Built automated Python and SQL pipelines to process large-scale transaction-level and firm-level financial data, improving reproducibility of analytical outputs
  • Designed and implemented an end-to-end NLP and OCR pipeline to extract structured information from complex M&A filings, reducing manual document review from ~2 hours to under 30 minutes per case
  • Applied dynamic panel data models to longitudinal financial behaviour datasets, addressing endogeneity and unobserved heterogeneity
  • Developed stakeholder-facing dashboards supporting evidence-based decision processes under resource constraints
  • Presented quantitative analyses to senior leadership, translating modelling outputs into clear, risk-based strategic recommendations
FEB 2021 — FEB 2023
Data Scientist
British Transport Police · London, UK
  • Developed statistical and predictive models to forecast operational risk and demand, supporting strategic resource allocation
  • Built reproducible data pipelines and analytical frameworks for large structured datasets
  • Delivered quantitative insights and visualisations to senior stakeholders
NOV 2020 — FEB 2021
Actuarial Analyst (Contract)
AIG · London, UK
  • Developed regression models and GLMs to price protection products
  • Conducted scenario and sensitivity analysis to assess pricing robustness
  • Automated actuarial processes, improving reporting efficiency by 10%
NOV 2018 — AUG 2019
Actuarial Assistant
The MDU · London, UK
  • Performed stress testing and scenario analysis to evaluate business resilience under adverse claim scenarios
  • Collaborated with data teams to improve financial reporting accuracy to 98%
DEC 2016 — NOV 2018
Reinsurance Analyst
Vitality Life · London, UK
  • Applied behavioural modelling techniques to support a direct sales project — findings presented at an actuarial conference, contributing to a 25% uplift in sales
  • Streamlined reinsurance reporting processes using R, reducing preparation time by 90%
NOV 2015 — DEC 2016
Household Pricing Analyst
Admiral Group · Cardiff, UK
  • Pricing model development and GLM analysis for personal lines household insurance
04 · Technical Skills

Stack &
tooling

Languages
  • Python
  • SQL
  • R
  • SAS
  • VBA
  • MATLAB
ML & Quant
  • Scikit-learn
  • XGBoost
  • NumPy / Pandas
  • Statsmodels
  • TensorFlow / PyTorch
  • spaCy / NLTK
  • Matplotlib
Platforms & Tools
  • Microsoft Azure
  • AWS
  • Excel / VBA
  • Power BI / Tableau
  • Spark
  • JIRA
  • Salesforce
Quant Methods
  • Panel Data Models
  • GLMs / Regression
  • Time-Series Forecasting
  • Monte Carlo Simulation
  • Stress & Scenario Testing
  • Rolling Validation
  • Factor Construction
05 · Education & Credentials

Academic
foundation

2021
Algorithmic Trading Programme
University of Oxford, Saïd Business School
78% · Certified
2019 – 2020
MSc Data Science
City University of London
Distinction
2011 – 2015
BSc Actuarial Science (Hons)
Cass Business School (Bayes), London
2017 – 2019
Actuarial Exams: CT1, CT2, CT3, CT5, CT7 & CB3
Institute and Faculty of Actuaries
Self-Funded
2022
Investment Management Certificate (IMC)
CFA UK
Certified
2026
CFA Level 1
CFA Institute
Candidate · Nov 2026

06 · Contact

Open to
the right conversations

Interested in quantitative research roles, systematic strategy development, and data science positions in financial services. Always open to academic collaborations in applied ML and finance.

hisho@rajanathan.com
LinkedIn ↗ GitHub ↗ Medium ↗