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Python For Finance Jobs in Quebec (NOW HIRING)

NavitasPartners

CA$30/hr

Python * Machine Learning * Scikit-learn * TensorFlow * PyTorch * Spark ML * Feature Engineering ... financial forecasting solutions. For more details reach at resumes@navitassols.com

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Worthland

Lead Risk Manager, Payment Fraud

Montreal, QC · Hybrid

$150K - $180K/yr

... Expert-level SQL for independent querying of large transactional datasets; strong Python ... financial security. Why This Role This is not a maintenance seat at a stagnant company. It is a ...

Worthland

Lead Risk Manager, Payment Fraud

Montreal, QC · Hybrid

$150K - $180K/yr

... Expert-level SQL for independent querying of large transactional datasets; strong Python ... financial security. Why This Role This is not a maintenance seat at a stagnant company. It is a ...

Soucy

Knowledge of calculation automation and simulation workflows (e.g., Python) * Interest in numerical ... An RRSP with employer contributions for financial stability * An Employee and Family Assistance ...

Soucy

... Python) Interest in numerical validation and correlation with experimental testing Benefits ... for financial stability An Employee and Family Assistance Program (EFAP) and access to telemedicine ...

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Python For Finance information

What is the difference between Python For Finance vs Quantitative Analyst?

AspectPython For FinanceQuantitative Analyst
Required CredentialsPython skills, finance knowledge, possibly finance-related certificationsAdvanced degrees (e.g., MSc, PhD) in finance, mathematics, or related fields; certifications like CFA
Work EnvironmentFinancial firms, trading desks, investment banks, hedge fundsFinancial institutions, hedge funds, asset management firms, consulting
Employer & Industry UsageUsed for developing trading algorithms, risk modeling, data analysisDevelops quantitative models, risk assessments, trading strategies

Python For Finance focuses on using Python programming to analyze financial data and develop models, often as a technical skill. Quantitative Analysts, however, apply advanced mathematical and statistical techniques to create complex financial models. While both roles require strong analytical skills, Quantitative Analysts typically have higher-level degrees and certifications, and their work involves more theoretical modeling. Python For Finance is often a skill within a Quantitative Analyst's toolkit, but the roles differ in scope and depth.

How does a Python for Finance professional typically collaborate with other departments within a financial organization?

Python for Finance professionals frequently work alongside departments such as data analytics, risk management, and portfolio management. They often translate complex financial models into scalable code, automate data processes, and support decision-making by providing actionable insights through data analysis. Effective communication and collaboration are essential, as these professionals must understand the specific needs of stakeholders and ensure that technical solutions align with business objectives. Regular meetings, code reviews, and cross-functional project teams are common structures within the work environment.

What is Python for Finance?

Python for Finance refers to the use of the Python programming language for financial analysis, modeling, trading, and data visualization. Financial professionals use Python to automate data processing, analyze large financial datasets, build quantitative models, and develop trading algorithms. Its vast ecosystem of libraries such as Pandas, NumPy, and Matplotlib makes Python a popular choice in the finance industry for tasks ranging from risk management to portfolio optimization.

What are the key skills and qualifications needed to thrive as a Python Developer in Finance, and why are they important?

To thrive as a Python Developer in Finance, you need strong programming skills in Python, a solid understanding of financial concepts, and often a degree in computer science, finance, or a related field. Familiarity with financial libraries (such as pandas, NumPy, and QuantLib), databases, and version control systems is typically required, and certifications in data science or finance can be advantageous. Analytical thinking, attention to detail, and effective communication are vital soft skills for interpreting financial data and collaborating with cross-functional teams. These skills are essential to develop robust financial solutions, ensure data accuracy, and drive informed decision-making in a highly regulated and data-driven industry.
Python For Finance jobs near you

Machine Learning Engineer (BFSI) - MLEBAS

NavitasPartners

On-site

CA$30/hr

Full-time

Posted 2 days ago

Job description

Job Title: Machine Learning Engineer (BFSI)

Position Overview:
The ML Engineer will develop, deploy, and optimize machine learning solutions supporting fraud detection, risk analytics, customer intelligence, and financial forecasting.

Key Responsibilities:

  • Develop machine learning models and pipelines.
  • Build feature engineering frameworks.
  • Deploy production-grade ML solutions.
  • Optimize model performance and scalability.
  • Collaborate with data scientists and business teams.
  • Implement model monitoring and governance.

Required Skills:

  • Python
  • Machine Learning
  • Scikit-learn
  • TensorFlow
  • PyTorch
  • Spark ML
  • Feature Engineering
  • Model Deployment
  • SQL

Required Qualifications:

  • Bachelor's or Master's degree in Data Science, AI, Computer Science, or related field.
  • 5+ years of machine learning experience.

Mandatory Industry Experience:

  • Must have prior BFSI experience delivering fraud detection, credit risk scoring, customer segmentation, anti-money laundering, underwriting, or financial forecasting solutions.


For more details reach at resumes@navitassols.com