Nathaniel Forde

Nathaniel Forde - Experienced Data Scientist / Statistician

Dublin, Ireland +353 86 052 5426 nathanielf.github.io nathaniel.forde@gmail.com

Profile

Expert Statistician/Data Scientist with 10+ years' experience delivering ML products — ranging across probabilistic modelling to causal inference in high-growth tech and regulated industries. Skilled in leading teams, scaling data platforms, and translating R&D into business impact. Open-source contributor (PyMC, Bambi, CausalPy, PyMC-Marketing) and experienced in experimentation strategy, MLOps, and customer-facing analytics.

Core Skills

  • ML / Statistics: Probabilistic AI, Causal inference, Bayesian methods, Time-series, Survival analysis, Factor analysis, Deep Learning, Survey Analysis, Marketing Analytics
  • MLOps & Cloud: AWS (SageMaker, Lambda, ECS, S3), ML pipelines, CI/CD, Docker, Spark, Statsig, Snowflake-ML
  • Data Tools: scikit-learn, PyMC, Pandas, dbt, PyTorch, Bambi, CausalPy, statsmodels
  • Leadership: Team growth (0→9), cross-functional influence, experimentation strategy, mentoring

Experience

Staff Data Scientist — PandaDocs, Dublin
August 2026 – Present
  • Leading on causal inference and experimentation strategy across the product led growth initiative.
Principal Data Scientist — PyMC Labs (Part-time Consulting)
2024 -Present
  • Advising on applied Bayesian statistics, causal inference, and probabilistic machine learning for enterprise projects.
  • Multiple +1M$ client engagements and policy recommendations across different retail sectors and markets.
Staff Data Scientist — Personio (HR SaaS), Dublin
April 2024 – August 2026
  • Scaled the data science org from 0→9 scientists, establishing hiring processes, best practices, and technical roadmaps.
  • Built and designed Proactive Insights and Engagement Survey products, driving product stickiness and upsell opportunities.
  • Designed and rolled out in-house experimentation framework; A/B testing adoption increased 3×, and test velocity improved 40% YoY after Statsig integration.
  • Led long-term forecasting and MMM models (revenue/costs) that improved planning accuracy by 5%, directly impacting company OKRs.
  • Mentored junior data scientists and set standards for documentation, modelling, and productionization of ML workflows. Adopted Manager role during Paternity cover period.
Senior Data Scientist — Personio (HR SaaS), Dublin
Nov 2021 – April 2024
  • Built Personio's first end-to-end ML deployment pipeline (Python/AWS), now serving 10+ live models.
  • Developed survival models (time-to-failure) used for reliability prioritization; reduced error by 5%.
  • Performed root-cause analytics with VAR models to diagnose UX latency issues, resulting in 35% improvement in customer-facing performance metrics.
  • Led experimentation with LLMs and NLP pipelines for customer feedback analysis, clustering customer sentiments at scale via latent space embeddings.
Data Scientist (R&D) — CarTrawler (E-commerce), Dublin
Nov 2019 – 2021
  • Designed dynamic pricing and demand forecasting models improving margin 4% and reducing loss ratios 8% YoY.
  • Built customer segmentation based on price sensitivity that fed into real-time pricing strategies.
  • Developed interlocking claim-propensity and loss-ratio forecasting models for insurance products.
  • Published work on Discrete Choice modelling for consumer preference.
Lead Insights Analyst — Paddy Power/Betfair (Gaming), Dublin
Feb 2018 – 2019
  • Created NLP models predicting sentiment on customer chat data during peak usage periods like Cheltenham
  • Built propensity models for Responsible Gambling interventions, influencing €5M in budget allocation.
  • Partnered with industry think tank on predictive models for problem gambling; findings shaped regulatory strategy.
  • Team Lead and Supervisor to Junior Analysts; responsibilities included annual planning and performance reviews.
Software Developer — Marsh & McLennan Innovation Centre (Insurance), Dublin
Mar 2017 – 2018
  • Developed web-apps (Go/Postgres/React) to deliver MCMC risk prediction models (earthquakes, floods, fires) to underwriters.
Data Analyst — Marsh & McLennan Innovation Centre (Insurance), Dublin
Mar 2014 – 2017
  • Built statistical metrics and dashboards improving data quality 15% across 20+ global business units.
  • Developed CRUD app (Shiny) for customer QA and spearheaded the company's first data quality framework.

Selected Publications & Open Source

Bayesian Vector AutoRegressive Models of Irish GDP — PyMC, Open Source
Dec 2022

Developed hierarchical Bayesian VAR & forecasting models. View on PyMC

Justifying Instruments in IV Designs — CausalPy, Open Source
Jun 2024

Core documentation on instrumental variable methods. View on CausalPy

Education

MSc Logic — University of Amsterdam (ILLC), Netherlands
2011 – 2013
  • Research thesis: models of causal inference and dependency relations.
MPhil (Research) Philosophy — Trinity College Dublin
2009 – 2011
  • Modal logics & identity; awarded IRCHSS Scholarship.
BA International — UCD / Sorbonne Université, Dublin & Paris
2005 – 2009

Leadership & Community

PyCon & PyData Speaker — PyCon Ireland & PyData Berlin
2023 – Present
  • Frequent mentor and speaker at PyCon events, Bayesian meetup groups, and internal data science guilds.
Hiring Strategy and People Management — Personio, Dublin
2021 – Present
  • Co-led Personio's data science hiring strategy: designed technical interview frameworks, improving candidate signal and DEI balance. Provided people management support and paternity coverage; including performance management and planning.
Open Source Contributor — PyMC ecosystem
2021 – Present
  • Contributor to open-source probabilistic programming and causal inference libraries with 100k+ total users.