Rowan Vance
Senior Data Scientist | Statistical Modelling & Production Machine Learning
Manchester
Executive Summary
Senior Data Scientist with extensive experience delivering production-grade machine learning systems and statistical solutions across logistics, healthcare, and enterprise analytics. Specialized in predictive modelling, causal inference, and translating complex mathematical concepts into measurable business decisions.
Demonstrated track record of technical leadership, model governance, and building reliable, scalable analytics pipelines within cross-functional engineering teams.
Professional Experience
NorthVantage Analytics
Manchester, United Kingdom
Lead Data Scientist
Mar 2021 – Present
- Lead the algorithmic design and production deployment of predictive modelling pipelines for retail and logistics clients across the UK.
- Architected a demand forecasting framework utilizing gradient-boosted trees and causal inference, reducing warehouse overstock by 14% across 8 distribution centres.
- Mentor a team of six mid-level and junior data scientists, establishing peer code review standards, unit testing practices, and reproducibility benchmarks.
- Collaborate with product managers and data engineering leads to transition batch ML workloads into low-latency event-driven microservices.
Pennine Health Informatics
Manchester, United Kingdom
Senior Data Scientist
Aug 2016 – Feb 2021
- Developed natural language processing models to extract clinical entities and risk indicators from unstructured diagnostic summaries.
- Supervised model governance, bias auditing, and model explainability using SHAP and counterfactual fairness methods in line with NHS compliance guidelines.
- Engineered survival analysis models to predict patient readmission likelihood, improving early intervention targeting by 18%.
Caldervale Digital Solutions
Salford, United Kingdom
Data Scientist
May 2012 – Jul 2016
- Built customer churn and segmentation algorithms using Python, PySpark, and Scikit-learn for commercial subscription services.
- Partnered with database administrators to optimize feature extraction queries on large-scale relational databases, decreasing pipeline execution time by 35%.
- Delivered technical briefings and executive dashboards interpreting model outputs to non-technical stakeholders.
Education
University of Manchester
Master of Science · Applied Statistics and Datamining · Manchester, United Kingdom · Distinction · Sept 1992 – Jul 1993
Specialised in multivariate analysis, time-series forecasting, and generalised linear models, completing a dissertation on non-stationary spatial distributions.
University of Leeds
Bachelor of Science (Honours) · Mathematics · Leeds, United Kingdom · First Class · Oct 1989 – Jun 1992
Focused on numerical methods, linear algebra, probability theory, and discrete computation.
Key Projects
Sequential Drift & Fairness Benchmark
Sept 2024 – Jun 2025
- Developed a Python-based open-source benchmark toolkit for evaluating fairness and drift in sequential classification models.
- Published modular evaluations comparing calibration metrics against traditional statistical thresholds across synthetic time-series datasets.
Skills
Python
Statistical Modelling
Machine Learning
SQL
PySpark
MLflow
Scikit-learn
Time-Series Analysis
Model Governance
Causal Inference
Languages
English
C2
French
B1
Certifications
Professional Machine Learning Engineer
Google Cloud · Apr 2024
Chartered IT Professional (CITP)
Chartered Institute for IT (BCS) · Nov 2021
Volunteering
Manchester STEM Community Network
Manchester, United Kingdom · Jan 2019 – Nov 2023
- Data Science Mentor
- Organised monthly technical workshops and study groups covering open-source data science tools, statistical modelling, and inclusive hiring practices.