Senior Data Scientist at Fingerprint

Job description

Fingerprint empowers enterprises to detect and stop online fraud with the world’s most accurate device intelligence. We lead our industry with bleeding-edge identification capabilities and work on turning new ideas and discoveries in the fraud detection space into reality. Our customers range from innovative startups to leading enterprise companies, including Plaid, Dropbox, and Booking.com. Fingerprint is a globally dispersed, 100% remote company. We were named on on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies. We have raised $77M and are backed by Craft Ventures ( Tesla, Facebook, Airbnb ), Nexus Venture Partners ( Postman , Apollo.io, MinIO , Druva) and Uncorrelated Ventures ( Redis, Rollbar, Gradle ). About the role We are seeking a Senior Data Scientist to join our innovative team. In this role, you will focus on improving the accuracy of the Fingerprint Pro Identification Service by applying advanced data science and machine learning techniques in a high-load real-time service setting. As a Senior Data Scientist, you will lead technical strategies, and contribute to fostering an engineering-focused, data-driven culture across the Fingerprint team. You will own data science projects from concept to deployment, ensuring they seamlessly integrate with our real-time identification platform. Responsibilities: Develop data-driven algorithms for the Fingerprint Identification Service, applying ML techniques to 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. Own data science projects end to end, from concept and experimentation through deployment into our real-time platform. Design experiments and solutions for ML engineering challenges such as real-time model inference and training pipeline automation. Conduct exploratory data analysis to investigate ad-hoc questions and address anomalous data. Help build an engineering-focused, data-driven culture across the team by sharing tools and effective approaches to data science. Participate in a shared on-call rotation. Schedules are communicated in advance, and we balance coverage equitably while minimizing off-hours disruption. This role includes participation in a shared on-call rotation. The schedule will be communicated in advance, and we strive to balance coverage equitably while minimizing off-hours disruptions. Qualifications: 5+ years of experience across machine learning, data science, and backend development. Advanced foundations in machine learning and statistical methodologies. Strong experience with 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 real-time inference and model-to-service integration. Ability to turn ML models into MVP real-time web services. Excellent coding skills, including SQL and general software engineering tools (Git, CI/CD pipelines, IDEs, shell scripting). Fluent English for clear communication in a global, remote team. Nice to have: An academic background and a research mindset. Backend development experience with Go. Experience with analytical storage systems such as ClickHouse, Snowflake, or BigQuery. Familiarity with engineering practices for maintaining data transformations, including frameworks like dbt. Hands-on experience with data visualization tools such as Apache Superset, Tableau, or Looker. Hands-on experience with vector databases (e.g., Pinecone, FAISS, Qdrant). Experience building and maintaining embedding-based search systems. Technologies you'll work with: Backend and data science: Go, SQL, and advanced ML frameworks Data processing and analytics: ClickHouse, dbt Infrastructure: AWS Compensation & Transparency For US-based employees, the cash compensation range for this role is $152,000 – $205,000. We set standard ranges for all US roles based on function, level, and geographic location, benchmarked against similar stage growth companies. To comply with local legislation and provide greater transparency, we share salary ranges on all job postings. However, these ranges are specific to the hiring location and may differ within or outside the US. Offers vary depending on, but not limited to, relevant experience, education, certifications/licenses, skills, training, and market conditions. Due to regulatory and security reasons, there's a small number of countries where we cannot have Fingerprint teammates based. Additionally, because Fingerprint is an all-remote company and people can join our workforce from almost any country, we do not sponsor visas. Fingerprint teammates need to be authorized to work from their home location. We are dedicated to creating an inclusive work environment for everyone. We embrace and celebrate the unique experiences, perspectives and cultural backgrounds that each employee brings to our workplace. Fingerprint strives to foster an environment where our employees feel respected, valued and empowered, and our team members are at the forefront in helping us promote and sustain an inclusive workplace. We highly encourage people from underrepresented groups in tech to apply. If you are applying as a resident of California, please read our CCPA notice here . If you are applying as a resident of the EU, please read our GDPR notice here . We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @ fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored.* Due to regulatory and security reasons, there’s a small number of countries where we cannot have Fingerprint teammates based. Additionally, because Fingerprint is an all-remote company and people can join our workforce from almost any country, we do not sponsor visas. Fingerprint teammates need to be authorized to work from their home location. We are dedicated to creating an inclusive work environment for everyone. We embrace and celebrate the unique experiences, perspectives and cultural backgrounds that each employee brings to our workplace. Fingerprint strives to foster an environment where our employees feel respected, valued and empowered, and our team members are at the forefront in helping us promote and sustain an inclusive workplace. We highly encourage people from underrepresented groups in tech to apply. If you are applying as a resident of California, please read our CCPA notice here . If you are applying as a resident of the EU, please read our GDPR notice here. **We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Fingerprint recruiting email communications will always come from the @fingerprint.com domain. Any outreach claiming to be from Fingerprint via other sources should be ignored.

Requirements

Must-haves

Fingerprint is a globally dispersed, 100% remote company. We were named on on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies.
We have raised $77M and are backed by Craft Ventures ( Tesla, Facebook, Airbnb ), Nexus Venture Partners ( Postman , Apollo.io, MinIO , Druva) and Uncorrelated Ventures ( Redis, Rollbar, Gradle ).
Develop data-driven algorithms for the Fingerprint Identification Service, applying ML techniques to 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.
Own data science projects end to end, from concept and experimentation through deployment into our real-time platform.
Design experiments and solutions for ML engineering challenges such as real-time model inference and training pipeline automation.
Conduct exploratory data analysis to investigate ad-hoc questions and address anomalous data.
Help build an engineering-focused, data-driven culture across the team by sharing tools and effective approaches to data science.
Participate in a shared on-call rotation. Schedules are communicated in advance, and we balance coverage equitably while minimizing off-hours disruption.
This role includes participation in a shared on-call rotation. The schedule will be communicated in advance, and we strive to balance coverage equitably while minimizing off-hours disruptions.
5+ years of experience across machine learning, data science, and backend development.
Advanced foundations in machine learning and statistical methodologies.
Strong experience with 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 real-time inference and model-to-service integration.
Ability to turn ML models into MVP real-time web services.

Nice-to-haves

An academic background and a research mindset.
Backend development experience with Go.
Experience with analytical storage systems such as ClickHouse, Snowflake, or BigQuery.
Familiarity with engineering practices for maintaining data transformations, including frameworks like dbt.
Hands-on experience with data visualization tools such as Apache Superset, Tableau, or Looker.
Hands-on experience with vector databases (e.g., Pinecone, FAISS, Qdrant).
Experience building and maintaining embedding-based search systems.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlsqlci/cdgoaws

Platform: greenhouse
Effort: quick