Lead Data Scientist

Summary

Join Fingerprint as a Lead Data Scientist and contribute to enhancing the accuracy of our Fingerprint Pro Identification Service. You will lead technical strategies, mentor engineers, and foster a data-driven culture. This role involves developing data-driven algorithms, implementing machine learning approaches, and conducting exploratory data analysis. You will own projects from concept to deployment, ensuring seamless integration with our real-time platform. The ideal candidate possesses extensive experience in machine learning, data science, and backend development, along with strong software engineering skills. We offer a globally dispersed, 100% remote work environment.

Requirements

• Experience: 7+ years in Machine Learning, Data Science, and backend development
• Advanced foundations in ML and statistical methodologies
• Strong experience in supervised learning, including gradient boosting and handling high-cardinality categorical data
• Practical experience with semi-supervised and unsupervised learning techniques
• Proficiency in exploratory data analysis and creative problem-solving for dataset collection and performance estimation in the absence of labeled data
• Strong expertise in real-time ML service development, including challenges like real-time inference and model-to-service integration
• Excellent coding skills with expertise in SQL and general software engineering tools (Git, CI/CD pipelines, IDEs, shell scripting)
• Ability to create MVP real-time web services from ML models
• Fluent English for clear communication in a global, remote team

Responsibilities

• Develop data-driven algorithms for Fingerprint Pro Identification Service, applying ML techniques to process raw, noisy, and unlabeled data to extract insights about browsers and devices
• Lead the design and implementation of supervised, semi-supervised, and unsupervised learning approaches to improve our identification capabilities
• Mentor team members in machine learning, data science, and analytics, enhancing the team’s technical expertise
• Conduct exploratory data analysis to investigate ad-hoc questions and address anomalous data
• Design experiments and solutions for ML-related engineering challenges like real-time model inference and training pipeline automation
• Help build an engineering-focused, data-driven culture across the team by sharing tools and effective approaches to data science

Preferred Qualifications

• Academic background and a research mindset
• Backend development experience with GoLang
• Experience with analytical storage systems like Clickhouse, Snowflake, or BigQuery
• Familiarity with engineering practices for maintaining data transformations, including frameworks like dbt
• Hands-on experience with data visualization tools like Apache Superset, Tableau, or Looker

Benefits

100% remote company