Senior ML Engineer, Finance

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

📋 Description

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

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

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

• Source and incorporate financial data from international nonprofit registries and third-party signals, including SimilarWeb and Facebook.

• Organize and store the enriched dataset in our internal database to ensure it is accessible and beneficial for the broader team’s 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 enhance scoring accordingly.

• Implement the scoring model and take ownership of integrating outputs into Salesforce in a clean and maintainable manner.

• Develop a scraper to monitor the websites of existing clients, ensuring that Fundraise Up tools are appropriately 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 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-oriented mindset: capability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV).

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

• Advanced SQL skills; capability to independently construct complex datasets in ClickHouse and work with MongoDB.

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

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

🏝️ Benefits

• Private medical insurance for the employee and their family.

• 20 paid vacation days per year.

• 15 paid public holidays per year.

• 5 company-paid sick leave days.

• English learning courses.

• Relevant professional education opportunities.

• Access to a gym or swimming pool.

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

• Co-working options available.

• Remote working arrangements.