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Informatics Developer

New York,NY

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1261 Informatics Developer jobs in New York,NY

New, Posted 18 hours ago
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Principal Quant Developer (MLOps)

Fidelity Investments

Hoboken, NJ 07030

~ 16 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

  • A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field
  • Six (6) years of experience as a Senior Quant Developer or similar role
  • Alternatively, a Master's degree (or equivalent foreign education) in the same fields
  • Four (4) years of experience as a Lead Quantitative Development or similar role
  • This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
  • Expert in Python with experience across the development stack (full stack)
  • Exposure to object-oriented programming (OOP) and design patterns
  • Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
  • A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
  • Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
  • Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
  • Proven ability to construct and manage robust data pipelines and event-driven workflows
  • Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
  • Experience in containerization with Docker and orchestration with Kubernetes
  • Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
  • Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
  • Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
  • Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
  • Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
  • Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
  • Awareness of responsible AI governance practices
  • Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
  • Demonstrated knowledge of mathematics, statistics, and quantitative finance
  • Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
  • Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
  • Domain knowledge in either equities, fixed income or alternative asset classes
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