Senior Python/Quantitative Developer
Remote: Latin America
Job Type: Full-time
Pay: USD salary
Exclusive FitNext: No
Company Stage: Series A
Company Overview
A Series A financial technology company helping financial advisers understand and manage investment risk. Its platform analyzes investment portfolios and transforms complex financial data into actionable insights advisers can use with their clients.
The company combines financial engineering, quantitative analysis, and software development to deliver reliable portfolio risk insights.
Challenge
We are looking for a Senior Python Engineer — Investment Risk to own the production code behind the platform’s investment-risk scores.
You will translate financial methodologies into reliable software, validate calculations, investigate unexpected results, and improve the integrity of a core financial product.
Working within an existing Python/Django application, you will initially focus on understanding the current scoring system, resolving recurring issues, and building automated validation infrastructure that makes future changes safer.
This role is particularly suited for an engineer who combines strong production Python engineering with practical knowledge of investments, portfolio risk, and financial data, and who is comfortable taking ownership of complex systems.
You will:
- Build and maintain production Python code implementing investment-risk calculations and scoring methodologies
- Work within an existing Django application, following engineering standards for testing, code review, CI, and database migrations
- Translate financial methodologies into reliable, repeatable, and scalable software
- Build automated validation frameworks comparing scoring outputs against reviewed reference cases for securities and portfolios
- Integrate validation checks into CI/CD pipelines to prevent incorrect changes from reaching production
- Investigate production scoring issues and identify whether root causes come from code, data, or methodology
- Reproduce customer-reported score anomalies using real portfolio data
- Improve investment classification by resolving straightforward errors and escalating complex cases to financial specialists
- Assess the impact of scoring or classification changes across securities, portfolios, and customers
- Implement safe deployments, staged releases, and verified rollback procedures
- Work with financial and engineering teams to improve scoring integrity and system reliability
- Document calculation logic, technical decisions, changes, and findings clearly
Must Have
- 3–5+ years of professional software engineering experience, including ownership of production systems after release
- Strong hands-on experience with Python and Django in production environments
- Experience with pandas, NumPy, and SQL for data processing and financial calculations
- Strong understanding of software engineering practices, including automated testing, code review, CI/CD, and database migrations
- Experience building or maintaining investment, portfolio, pricing, financial, or risk-analytics software
- Practical understanding of portfolio risk concepts, including volatility, correlation, concentration, and downside risk
- Ability to identify implausible financial calculations and investigate discrepancies
- Working knowledge of US investment instruments, including equities, fixed income, funds, ETFs, annuities, structured products, cash equivalents, and private assets
- Experience debugging existing production systems and safely modifying live financial data
- Ability to build automated validation using reference data or known expected results
- Strong ownership, problem-solving, and technical communication skills
- Experience with financial code that was deployed, used, and maintained — not only research notebooks or prototypes
- Advanced English communication skills
Nice to Have
- Experience with tax-aware investment analytics, including after-tax returns, cost basis, tax-aware sequencing, or tax-loss harvesting
- Experience with financial data providers, security identifiers, and asset classification taxonomies
- Experience building golden-data tests or reference-set validation frameworks
- Experience with large-scale data migrations, backfills, and idempotent processing
- Experience with portfolio management, wealth management, investment platforms, or financial advisory technology
- Familiarity with Django-based financial applications and complex calculation pipelines
- Experience developing diagnostic tools that enable other engineers to investigate production issues independently
- Knowledge of model governance, scoring integrity, and audit-ready documentation
Soft Skills - Ideal Profile
- Strong ownership and accountability for production systems
- Analytical and detail-oriented, particularly when working with financial calculations
- Comfortable investigating undocumented systems before making changes
- Methodical problem-solver who distinguishes code defects, data issues, and methodology gaps
- Able to work independently while knowing when to escalate complex financial decisions
- Pragmatic engineer who prioritizes reliability, correctness, and maintainability
- Clear communicator who can explain technical findings to engineers and financial specialists
- Comfortable working in a collaborative, remote environment
- Proactive, curious, and motivated to improve existing systems rather than simply maintain them
Benefits
- USD salary
- Fully remote across Latin America
- Full-time opportunity
- High ownership of a core financial product
- Direct collaboration with engineering and financial specialists
- Opportunity to improve the reliability and integrity of investment-risk calculations
- Work at the intersection of Python engineering, quantitative finance, investment analytics, and financial technology
- Opportunity to build foundational validation infrastructure and contribute to future tax-aware analytics
Interview Process
- Application Review
- Async Loom
- Screening Interview
- WHO Interview
- Focused Technical Interview
- Offer Extended
- Hired