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I'm David Cottrell, a data analytics lead with roots in physics and applied mathematics. I work at the intersection of modeling, infrastructure and product, especially where time matters: prediction, temporal modeling, and real-world inference under constraints. Most recently I led data and ML at a fintech focused on fixed income trading and analytics, building resilient systems that support iterative experimentation and rapid delivery in lean environments. I'm drawn to hard problems and fast-moving teams, particularly those building with AI and LLM tooling as part of modern workflows. I enjoy hands-on leadership and mentoring.…I'm David Cottrell, a data analytics lead with roots in physics and applied mathematics. I work at the intersection of modeling, infrastructure and product, especially where time matters: prediction, temporal modeling, and real-world inference under constraints. Most recently I led data and ML at a fintech focused on fixed income trading and analytics, building resilient systems that support iterative experimentation and rapid delivery in lean environments. I'm drawn to hard problems and fast-moving teams, particularly those building with AI and LLM tooling as part of modern workflows. I enjoy hands-on leadership and mentoring.

David Cottrell

Data Scientist, AI Engineer, Data Analyst, +1

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I'm David Cottrell, a data analytics lead with roots in physics and applied mathematics. I work at the intersection of modeling, infrastructure and product, especially where time matters: prediction, temporal modeling, and real-world inference under constraints. Most recently I led data and ML at a fintech focused on fixed income trading and analytics, building resilient systems that support iterative experimentation and rapid delivery in lean environments. I'm drawn to hard problems and fast-moving teams, particularly those building with AI and LLM tooling as part of modern workflows. I enjoy hands-on leadership and mentoring.…I'm David Cottrell, a data analytics lead with roots in physics and applied mathematics. I work at the intersection of modeling, infrastructure and product, especially where time matters: prediction, temporal modeling, and real-world inference under constraints. Most recently I led data and ML at a fintech focused on fixed income trading and analytics, building resilient systems that support iterative experimentation and rapid delivery in lean environments. I'm drawn to hard problems and fast-moving teams, particularly those building with AI and LLM tooling as part of modern workflows. I enjoy hands-on leadership and mentoring.

Available to hire

I’m David Cottrell, a data analytics lead with roots in physics and applied mathematics. I work at the intersection of modeling, infrastructure and product, especially where time matters: prediction, temporal modeling, and real-world inference under constraints.

Most recently I led data and ML at a fintech focused on fixed income trading and analytics, building resilient systems that support iterative experimentation and rapid delivery in lean environments. I’m drawn to hard problems and fast-moving teams, particularly those building with AI and LLM tooling as part of modern workflows. I enjoy hands-on leadership and mentoring.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Head of Data Analytics at Ediphy

July 1, 2025 - July 1, 2025

Led data analysis and technical reporting in support of Ediphy’s regulatory engagement around consolidated tape, producing market-structure studies and tooling that shaped dialogue with EU regulators and a successful bid. Built data pipelines and analytics infrastructure for fixed income and derivatives, handling normalization, deduplication, slicing, and storage. Delivered internal dashboards and refactored modeling systems for real-time quoting, pricing, smoothing, and mid-estimation. Developed probabilistic models for dealer behavior and trade evaluation to support RFQ workflows. Led R&D on sparse, irregular time series modeling using JAX/Equinox (e.g., kernel learning, IOU processes). Prototyped LLM- and OCR-based tools for automation and external API integration. Mentored across modeling, infra, and systems in a lean, hands-on team.

Director, Systematic Strategies, Research & Development at General Intelligence

June 1, 2020 - June 1, 2020

Led research on interday equity strategies using ML models for probabilistic forecasting and reinforcement learning. Built platform-agnostic research + production ML stack; adopted TensorFlow 2.0 early.

Director, Quant Data Analytics at UBS FRC (FX, Rates, Credit)

November 1, 2018 - November 1, 2018

Played a key role in scaling an internal data science team within Front Office, deeply involved in hiring, internal collaboration, and building analytics capabilities before and during a period of structural change. Designed distributed data pipelines for sales/trading analytics. Built markout predictors, book imputation models, clustering, and recommendation engines. Deployed infra using Spark, Dask, GlusterFS. Collaborated with FO and Treasury on intraday liquidity analytics.

Quant Analyst, Market Risk at Morgan Stanley

June 1, 2015 - June 1, 2015

Implemented calibration routines for ZABR/SABR risk factor generation. Delivered market risk solutions in Python/MATLAB with Scala interfaces.

Quant, Market Risk at Scotia Bank GBM

November 1, 2014 - November 1, 2014

Developed hVaR methodologies and full revaluation models (Basel). Supervised one direct report on futures risk models. Contributed to Front Office C++ risk library.