Susan Potter

### Quant Developer & Systematic Options Trader

Production-gradequant engineering

Quantitative infrastructure for systematic trading strategies. I build the tools that make edge repeatable: backtesting pipelines, strategy validation frameworks, and the type-driven code that holds them together.

25 years engineering software systems: from trading and risk platforms at Citadel, Bank of America, Morgan Stanley, and BNP Paribas, through building performance and analytics Software-as-a-Service (SaaS) products at Northern Trust, Salesforce, and Jive. Now I am back to quantative finance with algorithmic trading systems at Referential Labs, building strategy robustness validation, backtesting infrastructure, and portfolio risk analysis.


### What I Do
01

Quant Infrastructure

Backtesting pipelines, strategy validation frameworks, and data infrastructure built for correctness first.

  • QuestDB time-series storage
  • Robustness testing pipelines
  • Statistical validation
02

Strategy Validation

Quantitative, statistical, and econometric methods for validating algorithmic trading strategies.

  • Backtesting with zipline
  • pandas / polars pipelines
  • scipy statistical analysis
03 λ

Type-Driven Engineering

Large codebases that survive contact with production. FP correctness applied to financial systems.

  • Scala 3 / ZIO2 pipelines
  • Haskell domain modeling
  • Property-based testing
04

Distributed Systems

Trading and risk platforms, SaaS backends, and cloud-native infrastructure at scale.

  • AWS / Kubernetes / NixOS
  • High-availability systems
  • SRE & observability

### Current Focus

Backtesting & Validation Pipeline

Building infrastructure for validating algorithmic trading strategies using quantitative, statistical, and econometric methods. Robustness testing with QuestDB, Python, numpy, pandas, and zipline-reloaded.

Strategy Research

Applying quantitative methods to systematic strategy development. Using Pandas TA, scipy, polars, and quantdsl for signal generation and strategy validation.

Distributed Systems

25 years designing resilient distributed systems, from trading platforms at Citadel and Bank of America to SaaS backends at Northern Trust and Salesforce. Scala/ZIO, Haskell, and functional programming at scale.

Content & Writing

Author of the Git chapter in The Architecture of Open-Source Applications. Writing on functional programming, distributed systems, and quantitative methods.


### Writing
2024-11
Software Software Optimization Through Property-Based Thinking

Using always-true properties as optimization rules: reorder work, parallelize, or change data layouts while keeping behavior intact.

2023-06
Data Rapid Data Exploration with DuckDB

Lightning-fast analytics and data exploration using DuckDB's powerful query engine for datasets of any size.

2017-06
Economics Economic Concepts Applied in Software Development

Opportunity cost, comparative advantage, and thinking on the margins: economic principles for engineering decisions.


  • "Essentially, all models are wrong, but some are useful."

    G. E. P. Box
  • "Models are to be used, not believed."

    Often attributed to John W. Tukey
  • "The map is not the territory."

    Alfred Korzybski
  • "If you torture the data long enough, it will confess to anything."

    Ronald Coase
  • "Prediction is very difficult, especially about the future."

    Often attributed to Niels Bohr or Yogi Berra

### Technical Stack
Languages Python Scala Haskell TypeScript Erlang
Quant QuestDB pandas numpy polars zipline
FP ZIO 2 Cats Effect PureScript Property Tests
Infra AWS Kubernetes NixOS Terraform