Lead Python Developer – Quantitative Finance

1 week ago

Toronto, Ontario, Canada Global Applications Solution Full time $120,000 - $180,000 per year

Lead Python Developer (Tech Lead) – Quantitative Finance

Location:
Toronto, ON

Engagement:
Full-Time or Subcontract

Mode:
Hybrid (3 days onsite per week mandatory)

About the Role

We are seeking a highly skilled
Lead Python Developer
with strong expertise in
Quantitative Finance and Market Data Integration
. The successful candidate will lead the design and development of
high-performance, scalable reporting solutions
for
fixed-income pricing and risk metrics
, leveraging
the QuantLib
and
Bloomberg APIs
.

This role requires a strong blend of
technical depth, financial computation experience
, and
leadership ability
to drive analytics module development within a high-impact engineering team at the organization.

Key Responsibilities

  • Design, develop, and implement
    Python-based Quantitative Finance modules
    for:
  • Bond pricing
  • Yield curve modeling
  • Risk and performance analytics
  • Develop and maintain
    reusable QuantLib components
    for financial computations.
  • Integrate and validate
    Bloomberg API
    data and other market data sources.
  • Implement and optimize
    Quantitative Finance libraries
    (QuantLib, PyQL, finmath, etc.) for high-accuracy metric calculations.
  • Ensure precision and consistency (up to
    3-decimal accuracy
    ) across all risk and pricing computations.
  • Collaborate with
    data engineers
    and
    data analysts
    to ensure seamless integration with
    cloud-based data pipelines
    .
  • Lead
    Agile/Scrum
    development efforts and guide cross-functional teams on best coding and design practices.
  • Support
    testing, validation, and deployment
    of financial analytics modules in production environments.

Required Skills & Qualifications

  • 10+ years of professional experience
    in Python development, preferably within finance, risk analytics, or numerical computing.
  • Proven experience with
    Quantitative Finance libraries
    such as
    QuantLib
    ,
    PyQL
    , or equivalent.
  • Strong hands-on experience with
    Bloomberg APIs
    or other market data integration frameworks.
  • Deep understanding of
    fixed income instruments
    ,
    yield curves
    , and
    risk modeling concepts
    .
  • Expertise in
    numerical computation frameworks
    (NumPy, pandas, SciPy).
  • Solid knowledge of
    software design patterns
    ,
    API development
    , and
    scalable architecture
    .
  • Experience working in
    Agile/Scrum environments
    and leading small to mid-sized technical teams.
  • Excellent problem-solving, debugging, and communication skills.

Preferred Skills

  • Exposure to
    cloud data ecosystems
    (Azure, AWS, or GCP).
  • Familiarity with
    financial reporting
    and
    risk management systems
    .
  • Background in
    Quantitative Finance
    ,
    Applied Mathematics
    ,
    Computer Science
    , or
    Financial Engineering
    .

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