Senior ML Engineer, Finance

This is a fully remote position, open to applicants in Armenia.

📋 Description

• Create a market intelligence database by gathering various types of data (scraping, enrichment), repairing the data pipeline, and developing a machine learning model for scoring and analyzing raw data.

• Design and implement scrapers to gather essential signals from nonprofit websites, including utilized products, payment tools, and indicators of industry verticals.

• Develop essential filters, such as a binary classifier for "Is this website for fundraising?", along with additional features to identify high-potential prospects.

• Acquire and integrate financial information from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook.

• Organize and structure the enriched dataset within our internal database, ensuring it is accessible and beneficial for the broader team’s research and analysis efforts.

• Collaborate closely with the sales team to comprehend their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion trends and refine scoring accordingly.

• Deploy the scoring model and manage the integration of outputs into Salesforce in a clean, maintainable manner.

• Develop a scraper to monitor current clients' websites, ensuring that Fundraise Up tools are correctly implemented across their platforms.

⛳️ Requirements

• Over 5 years of experience in machine learning/data science addressing real product challenges.

• Strong proficiency in machine learning and mathematical statistics: comprehensive knowledge of classical algorithms (particularly gradient boosting) and an understanding of contemporary NLP/LLM methodologies.

• Demonstrated experience in large-scale web scraping and constructing data pipelines.

• Metrics-driven mentality: ability to correlate ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV).

• Strong engineering culture: proficient in Python with a product-focused approach; we prioritize clean code, familiarity with design patterns, and robust engineering practices.

• Advanced SQL skills; capable of independently creating complex datasets in ClickHouse and working with MongoDB.

• Understanding of MLOps: practical experience with experiment tracking and production workflows (Docker, Git, CI/CD).

• Autonomy: ability to deconstruct ambiguous problems, select the appropriate tech stack, and deliver to production efficiently.

🏝️ Benefits

• 31 days of paid time off.

• Comprehensive telemedicine plan fully covered by the company.

• Home Office Setup Assistance: the company provides support for purchasing furniture (office chair, office desk, monitor) and other items to establish a comfortable working environment.

• English language courses available.

• Opportunities for relevant professional education.

• Access to a gym or swimming pool.

• Co-working space options.

• Flexibility for remote work.