Data Scientist

Fingerprint is looking for a Data Scientist to help improve the accuracy of our Smart Signals by applying data science and machine learning techniques in a high-load, real-time service environment.

You’ll collaborate with engineers and data scientists on challenging ML problems and work across the project lifecycle from prototyping to deployment.

What You’ll Work On

• Develop algorithms that transform raw, noisy, and unlabeled data into insights about browsers and devices
• Design and implement supervised learning models to improve detection accuracy
• Partner with ML Engineers, Data Scientists, and Software Engineers to push forward our technical expertise
• Conduct exploratory data analysis to investigate anomalies and ad-hoc questions
• Run experiments to solve ML engineering challenges like real-time inference and training automation

What We’re Looking For

• BS or MS in Computer Science, Data Science, or related field, or equivalent experience
• 2–4 years of experience in Data Science or Machine Learning
• Strong foundations in ML and statistics
• Experience with supervised learning methods (gradient boosting, logistic regression, etc.) and working with categorical data
• Skilled in exploratory data analysis and deriving insights from complex datasets
• Proficiency in Python and SQL; experience with Git and software engineering basics
• Comfortable communicating in English in a global, remote team

Nice to Have

• Familiarity with semi-supervised or unsupervised learning techniques
• Hands-on experience with visualization tools (Apache Superset, Tableau, Looker)
• Knowledge of analytical storage systems (ClickHouse, Snowflake, BigQuery)
• Experience maintaining data transformations with dbt
• Ability to build lightweight real-time services from ML models
• Academic or research background

Tech Stack

• Backend & Data Science: Python, Go, SQL, ML frameworks
• Analytics & Processing: ClickHouse, dbt
• Infrastructure: AWS