Senior Data Scientist – Real‑Time Identification Platform

About the role

This senior, hands‑on data science position focuses on improving the accuracy and intelligence of a high‑volume, real‑time identification platform. You will work with complex, noisy, and often unlabeled data to develop machine learning approaches that distinguish browsers and devices with greater precision. The role is fully remote and combines advanced ML, statistical analysis, experimentation, and backend engineering.

Key responsibilities

• Develop data‑driven algorithms using raw, noisy, and unlabeled data to enhance browser and device identification.
• Design and implement supervised, semi‑supervised, and unsupervised ML models, including techniques for high‑cardinality categorical data.
• Own end‑to‑end data science initiatives from problem definition through production deployment and real‑time service integration.
• Build and maintain real‑time inference pipelines, model‑to‑service integration, and training automation.
• Conduct exploratory data analysis, detect anomalies, and evaluate model and dataset performance.
• Collaborate with engineering teams to turn ML concepts into reliable production services and participate in on‑call rotation.

Required profile

• 5+ years of professional experience in machine learning, data science, and backend development.
• Advanced knowledge of ML fundamentals, statistical methodologies, and experience with gradient boosting and high‑cardinality data.
• Proven ability to develop real‑time ML services and transform models into production‑ready web services.
• Strong coding skills, SQL expertise, and familiarity with Git, CI/CD pipelines, IDEs, and shell scripting.
• Fluent English communication and ability to work in a distributed international environment.

Required skills

• Machine learning frameworks (gradient boosting, semi‑supervised and unsupervised techniques)
• Programming languages: Go, SQL
• Version control and CI/CD: Git, pipelines
• Cloud and data platforms: AWS, ClickHouse, Snowflake, BigQuery
• Data transformation: dbt
• Visualization and search tools: Superset, Tableau, Looker, Pinecone, FAISS, Qdrant

What we offer

• Competitive compensation: $152,000–$205,000 USD per year (location‑specific).
• Fully remote working environment.
• Opportunity to solve challenging real‑time ML problems at scale.
• Exposure to modern ML, data engineering, backend development, and cloud infrastructure.
• Influence technical strategy and contribute to engineering and data‑science practices.
• Inclusive, globally distributed team with balanced on‑call rotation.