Staff Backend Engineer

Summary

Join Fingerprint, a globally dispersed, 100% remote company, as a Staff Backend Engineer with Data Science skills. You will lead the development of end-to-end fraud detection solutions, combining backend software development with data analysis. This role involves designing and implementing scalable backend systems, analyzing large datasets to detect fraudulent activity, and collaborating with cross-functional teams. You will leverage data engineering techniques, and experience with machine learning is a plus. The position offers a competitive salary range of $150,000 - $200,000 and the opportunity to work on impactful projects within a data-driven culture.

Requirements

• BS/MS in Computer Science, Data Science, or a related field, or equivalent work experience
• 8+ years of experience in backend development with exposure to data science
• Strong experience in designing, developing, and maintaining scalable backend systems
• Experience working with real-time data processing and APIs
• Excellent coding skills, particularly in GoLang (or equivalent), with working knowledge of data engineering practices
• Strong knowledge of SQL and experience with databases like DynamoDB, Redis, or Elasticsearch
• Proficiency with general software engineering tools: Git, IDEs, shell scripting, CI/CD
• Proficient in English for clear communication in a global, remote team

Responsibilities

• Develop and maintain backend services for fraud detection
• Design and implement scalable, high-performance backend systems, ensuring smooth integration with other components
• Take ownership of features from concept to final deployment, working closely with cross-functional teams to deliver reliable and robust solutions
• Analyze large datasets of traffic to uncover patterns and detect fraudulent activity
• Leverage data engineering techniques to process and manage large traffic datasets efficiently, find new ways to detect fraud, and implement them in backend code
• Collaborate with the Smart Signals Product team to improve fraud detection signals, including browser bot detection, VM detection, VPN detection, and more
• Conduct deep dives into problematic features, researching and analyzing their behavior to understand root causes and identify potential solutions. Develop hypotheses, run experiments, analyze results, and translate findings into actionable engineering improvements
• Build and enhance backend systems for real-time data processing
• Foster a data-driven culture by sharing engineering best practices and collaborating on cross-functional projects

Preferred Qualifications

• Practical experience with analytical storage systems like ClickHouse, Snowflake, BigQuery, Redshift, or Databricks
• Experience with data transformation frameworks like dbt or other data pipeline tools
• Familiarity with data visualization tools such as Apache Superset, Tableau, or Looker
• Experience with the Python data analytics stack (NumPy, Pandas, Jupyter, etc.)
• Familiarity with supervised and unsupervised learning methods
• Experience working with machine learning pipelines, model deployment, and performance monitoring
• Understanding of core ML concepts such as feature engineering, model evaluation, and real-time inference

Benefits

• $150,000 - $200,000 cash compensation
• 100% remote work