Senior Data Scientist

This is a senior, hands-on data science role focused on improving the accuracy and intelligence of a high-volume, real-time identification platform. You’ll work with complex, noisy, and often unlabeled data to develop machine learning approaches that distinguish browsers and devices with greater precision. The role combines advanced machine learning, statistical analysis, experimentation, and backend engineering in a highly technical environment. You’ll own projects from initial research and experimentation through production deployment and integration with real-time services. You’ll also help shape engineering practices, data-driven decision-making, and effective approaches to machine learning across the wider team. This is a fully remote opportunity suited to someone who enjoys solving challenging problems where research, software engineering, and applied ML meet.

• 5+ years of professional experience spanning machine learning, data science, and backend development or closely related engineering disciplines.

• Advanced knowledge of machine learning fundamentals and statistical methodologies.

• Strong practical experience with supervised learning, including gradient boosting and approaches for high-cardinality categorical data.

• Hands-on experience with semi-supervised and unsupervised learning techniques.

• Strong exploratory data analysis and creative problem-solving skills, particularly when working with incomplete, noisy, or unlabeled datasets.

• Proven experience developing real-time machine learning services, including model inference and integration between models and production applications.

• Ability to transform machine learning models into minimum viable real-time web services and production-ready solutions.

• Excellent coding and software engineering skills, including strong SQL capabilities and familiarity with Git, CI/CD pipelines, IDEs, and shell scripting.

• Strong communication skills and fluent English, with the ability to collaborate effectively in a distributed international environment.

• A research mindset and academic background are advantageous.

• Experience with Go and backend development is a plus.

• Familiarity with analytical data platforms such as ClickHouse, Snowflake, or BigQuery is beneficial.

• Experience with data transformation frameworks such as dbt, visualization tools such as Superset, Tableau, or Looker, or vector databases such as Pinecone, FAISS, or Qdrant is a plus.

• Experience building embedding-based search systems is advantageous.

• Familiarity with technologies such as Go, SQL, advanced ML frameworks, ClickHouse, dbt, and AWS is beneficial.