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We are looking for an experienced, highly motivated Python developer with expertise in building robust data pipelines, creating and manipulating DataFrames, and turning defined specifications into reliable, production-grade scripts. The role centres on developing and orchestrating the data infrastructure behind a systematic research platform: document analysis engines that extract structured data from financial filings and disclosures, integrated with market and transaction datasets into a point-in-time research database. This is a genuine opportunity to extend into quantitative research and to help build the foundation for full-stack, next-gen SaaS service offerings.
Key Responsibilities
- Bulletproof script development: build reliable, production-grade scripts from defined specifications.
- Data orchestration and integration: develop and own the orchestration scripts that integrate multiple data feeds (document analysis output, transaction data, market data) into the existing point-in-time database on a reliable schedule, continuously improving the dataset's quality and coverage.
- Document analysis engines: develop and improve engines that turn financial filings and disclosures into structured, queryable data, including LLM-assisted extraction where appropriate.
- Testing to production migration: own the path from development to production, testing rigorously in a staging environment before migrating scripts to the production server with proper versioning, rollback capability, and zero disruption to live processes.
- Data hygiene, processing, and transformation: apply disciplined data hygiene across sources, including deduplication, entity and identifier mapping, and handling of missing or malformed values, with close attention to point-in-time integrity (as-of date versioning, no look-ahead bias, clean handling of revisions).
- Automation and optimisation: automate data workflows and build in data quality checks so parsing failures, gaps, or stale data are caught before they reach research.
- Documentation and code quality: write well-documented, maintainable code with unit tests covering data processing and integration scripts. Clear, thorough documentation of what's built, how it works, and how to run it is a core part of the role, so work can be understood, maintained, and handed over by others.
- Foundation development: contribute to backend API development, user authentication, and database integration, laying groundwork for a scalable SaaS platform.
- Any other ad hoc duties: that may be required from time to time
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Technical Requirements
- Proven experience with Python, especially Pandas and NumPy
- Mastery of SQL and PostgreSQL: schema design, complex queries, indexing, and performance optimization, beyond basic querying
- Experience with pipeline orchestration and scheduling
- Proven ability to deliver reliable, tested scripts against a written specification, and to migrate them cleanly from a test environment to a production server
- Strong data hygiene, processing, and cleaning skills, including experience with messy real-world data (documents, filings, PDFs, HTML, third-party APIs)
- A habit of documenting your own work thoroughly, so others can understand, maintain, and build on it
- LLM API experience for structured data extraction, and general comfort working with AI tools and prompting
- An understanding of point-in-time data is a strong plus
Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining, and extending existing models; Bloomberg API integration to Python; data science/statistics, signal research, backtesting, or factor modelling; full-stack familiarity (Flask, Django, FastAPI); SaaS build/deploy on cloud (Docker, AWS, or similar); an understanding of Java; and experience in quantitative finance or with financial market data.
Qualifications & Experience
- Bachelor's or Master's in Computer Science, Data Science, IT, Electrical Engineering, or equivalent experience is essential
- Experience working in a regulated financial services industry, preferable but not essential
- Proactive approach towards identifying opportunities for improvement and taking ownership to deliver solutions
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About Us
Alvar Financial Services is a boutique firm offering a variety of investment and trading services through its business lines - Equity Markets for professional and institutional clients, Research Services, and Electronic Global Retail Platform for private clients. Our small community and flat structure empower our people to grow and create unconstrained ideas within their field of expertise, driving innovation and mastery in their work. We all work together as one to achieve our vision of being a trusted partner to our clients, providing unrivalled insights and a collaborative high-touch service.
Commitment To Diversity
At Alvar, we believe that every voice matters. We strive to create a mindful and respectful environment where everyone can bring their authentic self to work, and experience a culture that is free of harassment, racism, and discrimination. That’s why we are committed to diversity and inclusion in the workplace and are a proud equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic protected by law. This policy applies to all employment practices within our organisation, including, but not limited to, hiring, recruiting, promotion, termination, layoff, and leave of absence.
Alvar Financial Services is also committed to providing reasonable accommodations in our job application procedures for individuals with disabilities. Please inform our HR Team via email hr@alvarfinancial.com if you need any assistance completing any forms or to otherwise participate in the application process.
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