Fingerprint is looking for a Data Scientist to help improve the accuracy of their Smart Signals by applying data science and machine learning techniques in a high-load, real-time service environment.
Requirements
- 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
- Familiarity with semi-supervised or unsupervised learning techniques
- Ability to build lightweight real-time services from ML models
Responsibilities
- 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
Other
- BS or MS in Computer Science, Data Science, or related field, or equivalent experience
- Comfortable communicating in English in a global, remote team
- Hands-on experience with visualization tools (Apache Superset, Tableau, Looker)
- Knowledge of analytical storage systems (ClickHouse, Snowflake, BigQuery)
- Experience maintaining data transformations with dbt
