Data Scientist, Audio Telemetry Intelligence

We are seeking a Data Scientist to help advance telemetry intelligence for device experience optimization. This role focuses on analyzing large-scale audio session and device telemetry data to uncover patterns in user behavior and system adjustments, enabling opportunities for predictive and adaptive system improvements. The ideal candidate combines strong data analysis and programming skills with experience working with large-scale datasets. This role will partner with data scientists and engineers to build reliable datasets, develop analytical workflows, and translate telemetry insights into data-driven improvements to device audio experiences. Analyze large-scale audio session and device telemetry data to identify patterns in user behavior and system adjustments. Develop analytical datasets and workflows that support scalable analysis and experimentation. Build and maintain data pipelines that transform raw telemetry into reliable analytical datasets. Explore opportunities for predictive or adaptive system behaviors that improve device audio experience. Partner with engineering and product teams to translate telemetry insights into actionable product improvements. Improve data accessibility and reliability through automation and internal data tooling. Support experimentation and data-driven decision making across audio and device interaction scenarios. Bachelor’s or Master’s degree in Data Science, Machine Learning, Data Engineering, Computer Science, or a related quantitative field. 3+ years of full-time professional experience in data science, data engineering, or machine learning related roles. Strong programming skills in Python for data analysis, scripting, and automation. Advanced SQL skills for querying and analyzing large-scale datasets. Experience building or maintaining data pipelines and ETL/ELT workflows. Experience working with large-scale or distributed data processing frameworks (e.g., Apache Spark). Solid understanding of data modeling, data quality, and analytical dataset development. Proven work experience with applying statistical analysis or machine learning techniques to behavioral datasets. Experience working with telemetry, or time-series data. Familiarity with predictive modeling or pattern detection in large-scale data. Experience working with real-time or streaming data pipelines. Experience using AI-assisted development tools Proven experience working with large-scale data platforms or cloud-based data infrastructure. Strong communication skills with the ability to translate complex data insights into actionable recommendations. Experience using version control systems such as Git in collaborative environments.

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