Lead Quantitative Developer​/Engineer

One Concern
Los Angeles, US

Why this role

Pace
Fast Paced
Collaboration
High
Autonomy
High
Decision Impact
Company
Role Level
Team Lead

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design and enhance systematic research and trading infrastructure
  • implement and maintain backtesting frameworks
Typical background
7+ years of experience working in a backend role3+ years of experience working as a lead in a technical team

Transferable backgrounds

  • Coming from algorithmic-trading
  • Coming from risk-management

Skills & requirements

Required

PythonData StructuresAlgorithmsSoftware DesignFinancial Market DataTime SeriesBacktestingProduction SystemsMachine Learning Methods

Preferred

Hedge Fund ExperienceSystematic Trading StrategiesTechnical Lead ExperienceSQLCloud InfrastructurePortfolio ConstructionRiskExecution SystemsMathStatisticsPhysicsEngineering

Stack & domain

PythonFinancial Market DataTime SeriesQuantitative Research WorkflowsBacktestingData IngestionCleaningNormalizationStorageMachine LearningAi-driven ApproachesResearch WorkflowsData PipelinesInternal ToolsModel ImplementationIterationMonitoringDebuggingImproving Live StrategiesFeature EngineeringSignal DevelopmentAi-enabled Research And Productivity ToolsModel ExperimentationData AnalysisInternal ToolingCollaborationProblem-solvingTechnical Decision-makingCommunicationTeamworkQuantitative ResearchSoftware EngineeringTrading Operations

About the role

Original posting from One Concern

Position: Lead Quantitative Developer / Engineer

We are a growing stealth-mode fully-remote hedge fund focused on systematic and data-driven investment strategies. As we scale our research and trading capabilities, we are hiring a Quantitative Developer to help build and own the core research and trading infrastructure alongside the current team.

This is a high-impact role with significant autonomy and direct influence on how strategies are researched, implemented, and deployed.

Role Overview :

You will work closely with a lean team of our portfolio manager and quantitative researcher team to design, build, and maintain the systems that power our quantitative investment process. This role sits at the intersection of quantitative research, software engineering, and trading operations.

You will help turn research ideas into robust, production-ready systems and shape the technical foundation of the firm.

You will also contribute to the evaluation, implementation, and scaling of machine learning and AI-driven approaches that have contributed to alpha, spanning research workflows, data pipelines, and internal tools, in collaboration with other teams at the firm.

Key Responsibilities:

  • 1. Design and enhance our current systematic research and trading infrastructure
  • 2. Implement and maintain backtesting frameworks and research pipelines
  • 3. Productionize quantitative strategies and support live trading systems
  • 4. Work with large financial datasets (market data, fundamentals, alternative data)
  • 5. Optimize performance, reliability, and scalability of research code
  • 6. Build tools for data ingestion, cleaning, normalization, and storage
  • 7. Collaborate closely with PMs on model implementation and iteration
  • 8. Assist with monitoring, debugging, and improving live strategies
  • 9. Support the integration of machine learning techniques into quantitative research, feature engineering, and signal development
  • 10. Support the building and maintenance of AI-enabled research and productivity tools (e.g., model experimentation, data analysis, internal tooling)

Required Qualifications:

  • 1. 7+ years of experience working in a backend role
  • 2. 3+ years of experience working as a lead in a technical team
  • 3. 5+ years of experience working with Python
  • 4. Solid understanding of data structures, algorithms, and software design
  • 5. Experience working with financial market data and time series
  • 6. Familiarity with quantitative research workflows and backtesting
  • 7. Experience building or maintaining production systems
  • 8. Ability to work independently and make sound technical decisions
  • 9. Ability to work collaboratively with quantitative researchers and developers
  • 10. Familiarity with machine learning methods (e.g., regression, tree-based models, neural networks) and their application to financial data

Preferred / Nice to Have:

  • 1. 3+ years of experience in a hedge fund, prop trading firm, or quantitative asset manager
  • 2. 3+ years of exposure to systematic trading strategies (equities, futures, FX, or crypto)
  • 3. 3+ years of experience working as a technical lead
  • 4. Experience with performance optimization (vectorization, multiprocessing, etc.)
  • 5. Knowledge of SQL, cloud infrastructure (GCP/AWS), or distributed systems
  • 6. Understanding of portfolio construction, risk, or execution systems
  • 7. Background in math, statistics, physics, or engineering

What Makes This Role Unique:

  • 1. Technical hire joining an early hedge fund team with the ability to have significant ownership and influence
  • 2. Direct collaboration with decision-makers (PMs and leadership)
  • 3. Opportunity to shape architecture, tools, and best practices
  • 5. Exposure to the full lifecycle: research → production → trading
  • 6. Opportunity to work on applied AI initiatives and collaborate across the firm on AI-driven research and engineering efforts, alongside core quantitative trading systems.
  • 7. Competitive compensation with strong upside for the right candidate

We are an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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Source: One Concern careers

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