NPAworldwide
Job Description
Quantitative Developer role based in San Francisco, requires in‑office presence 5 days a week.
Key Responsibilities
Design and implement robust data pipelines and tools that bring quantitative research into production (e.g., Dagster, Spark, AWS).
Partner with research teams to ensure style factor research outputs are scalable, testable, and integrated into broader systems.
Own problem‑solving tasks such as automating research workflows, enabling scalable data access, or resolving cross‑system compatibility issues.
Contribute as a generalist across the entire pipeline from ingestion and transformation to orchestration and tooling.
Maintain a high standard of engineering quality across data handling, software design, and research tooling.
Work autonomously while acting as a reliable partner to quantitative researchers, identifying gaps, solving integration issues, and suggesting improvements.
Qualifications
Strong Python development skills, emphasizing clean, testable, and efficient code.
Deep understanding of data manipulation libraries such as Pandas and Polars.
Experience with SQL and non‑SQL databases such as Postgres, Redis, or Mongo.
Familiarity with distributed computing frameworks such as Apache Spark.
Hands‑on experience with AWS or similar cloud platforms.
Previous experience in quantitative research environments (financial, academic, or ML‑driven).
Experience supporting production workflows, ideally using modern orchestration tools such as Dagster or Airflow.
Ability to think holistically across systems and ensure alignment across the research and production stack.
Strong independent problem‑solving instincts.
Why This Is a Great Opportunity Core to the investment engine: The quant and technical team sits inside the investing system and works directly with PMs, quants, risk, and trading. Your work impacts PnL, decision quality, and speed.
Clean sheet environment with real ownership: Systems, tooling, and workflows are still being designed and improved, offering real influence rather than incremental tweaks.
Integration beats silos: Fundamental and quantitative professionals operate as one team; engineers and quant developers understand investment context.
Elite leadership with scale and credibility: Founders have experience at Citadel; you receive institutional rigor without the bureaucracy of a mature multi‑manager fund.
Real assets, real momentum: Fund launched with $3.5B, scaled to $11.6B by Q1 2025, operating at meaningful scale.
Engineering that matters: Heavy Python, systems touching alpha capture, transaction cost analysis, research tooling, and production deployment. Technical glue between models and execution.
Broad exposure without being spread thin: Runs a market neutral, multi‑strategy equity book across 6 sectors; focus on coverage without chaos of many teams.
High bar, serious peers: Team spans data science, AI, engineering, investing, risk, and trading.
Strong fit for a Python‑first quant developer: If you are a strong Python engineer who understands equities and wants to be closer to the investment process.
Seniority level
Entry level
Employment type
Full‑time
Job function
Finance and Sales
Industries
Staffing and Recruiting
Location & Compensation San Francisco, CA – Salary range: $100,000 – $195,000 annually.
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Key Responsibilities
Design and implement robust data pipelines and tools that bring quantitative research into production (e.g., Dagster, Spark, AWS).
Partner with research teams to ensure style factor research outputs are scalable, testable, and integrated into broader systems.
Own problem‑solving tasks such as automating research workflows, enabling scalable data access, or resolving cross‑system compatibility issues.
Contribute as a generalist across the entire pipeline from ingestion and transformation to orchestration and tooling.
Maintain a high standard of engineering quality across data handling, software design, and research tooling.
Work autonomously while acting as a reliable partner to quantitative researchers, identifying gaps, solving integration issues, and suggesting improvements.
Qualifications
Strong Python development skills, emphasizing clean, testable, and efficient code.
Deep understanding of data manipulation libraries such as Pandas and Polars.
Experience with SQL and non‑SQL databases such as Postgres, Redis, or Mongo.
Familiarity with distributed computing frameworks such as Apache Spark.
Hands‑on experience with AWS or similar cloud platforms.
Previous experience in quantitative research environments (financial, academic, or ML‑driven).
Experience supporting production workflows, ideally using modern orchestration tools such as Dagster or Airflow.
Ability to think holistically across systems and ensure alignment across the research and production stack.
Strong independent problem‑solving instincts.
Why This Is a Great Opportunity Core to the investment engine: The quant and technical team sits inside the investing system and works directly with PMs, quants, risk, and trading. Your work impacts PnL, decision quality, and speed.
Clean sheet environment with real ownership: Systems, tooling, and workflows are still being designed and improved, offering real influence rather than incremental tweaks.
Integration beats silos: Fundamental and quantitative professionals operate as one team; engineers and quant developers understand investment context.
Elite leadership with scale and credibility: Founders have experience at Citadel; you receive institutional rigor without the bureaucracy of a mature multi‑manager fund.
Real assets, real momentum: Fund launched with $3.5B, scaled to $11.6B by Q1 2025, operating at meaningful scale.
Engineering that matters: Heavy Python, systems touching alpha capture, transaction cost analysis, research tooling, and production deployment. Technical glue between models and execution.
Broad exposure without being spread thin: Runs a market neutral, multi‑strategy equity book across 6 sectors; focus on coverage without chaos of many teams.
High bar, serious peers: Team spans data science, AI, engineering, investing, risk, and trading.
Strong fit for a Python‑first quant developer: If you are a strong Python engineer who understands equities and wants to be closer to the investment process.
Seniority level
Entry level
Employment type
Full‑time
Job function
Finance and Sales
Industries
Staffing and Recruiting
Location & Compensation San Francisco, CA – Salary range: $100,000 – $195,000 annually.
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