Senior ML Engineer, Finance

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

📋 Description

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

• Design and manage scrapers to extract essential signals from nonprofit websites, including utilized products, payment methods, and industry vertical indicators.

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

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

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

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

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

• Develop a scraper to monitor existing clients' websites, ensuring that Fundraise Up tools are properly 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: solid understanding of classical algorithms (particularly gradient boosting) and familiarity with contemporary NLP/LLM methodologies.

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

• Metrics-driven approach: capability to link machine learning metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV).

• Strong engineering culture: proficient in Python with a product-oriented focus; we value clean code, knowledge of design patterns, and robust engineering practices.

• Advanced SQL skills; ability to independently create complex datasets in ClickHouse and work 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 solutions to production.

🏝️ Benefits

• 31 days of vacation.

• Fully covered telemedicine plan.

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

• Courses for English language learning.

• Relevant professional education opportunities.

• Access to gym or swimming pool.

• Co-working space availability.

• Option for remote work.