Senior Data Scientist

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🕒 April 10

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Clear-Com

WebsiteLinkedInAll Job Openings

51 - 200 employees

Clear-Com®, an HME company, is the global leader in professional voice communication systems for live productions. Since 1968, we have developed and marketed proven intercom technologies such as Analog Partyline, Digital Matrix, Digital Wireless and IP Communications systems for broadcast stations, production trucks, houses of worship and performance venues. Recognized for our legacy of intercom innovations, production teams around the world have come to depend on Clear-Com for clear, reliable and scalable communication solutions.

📋 Description

• Design and execute data science experiments such as causal analysis, A/B tests, and offline evaluations to validate product and underwriting decisions. • Develop, evaluate, and iterate on predictive models (e.g., credit/risk scoring, revenue forecasting, policy performance). • Own model performance and monitoring: define success metrics, investigate drift, and drive improvements to data quality and feature reliability. • Partner with Product Engineering to productionize models and analytics, focusing on reliability, reproducibility, and maintainability. • Turn messy real-world data into usable signals through exploratory analysis, feature engineering, and robust validation. • Clearly communicate insights to both technical and non-technical stakeholders through documentation and presentations. • Raise the bar for technical quality via improved analytical standards, code review practices, and documentation. • Mentor and support other team members through pairing, feedback, and sharing best practices.

🎯 Requirements

• 5+ years of professional experience in data science, applied machine learning, or a related quantitative role • Strong foundations in statistics and experimentation (hypothesis testing, causal reasoning, bias/variance tradeoffs, evaluation design) • Proven experience building and shipping predictive models (classification, regression, time series, etc.) and measuring real-world impact • Proficiency in Python and SQL, with comfort working with production data workflows • Comfortable working with stakeholders to define problems, align on success metrics, and deliver outcomes end-to-end • Strong written communication skills and a pragmatic approach to fast-moving environments • Nice to Have: Experience with credit risk, underwriting, fraud/risk signals, or financial forecasting, familiarity with modern data tooling and warehouses (e.g., BigQuery, Snowflake) and transformation frameworks (e.g., dbt), experience with MLOps patterns (model deployment, monitoring, feature stores, orchestration) and cloud environments, experience working with messy third-party data sources (banking data, eCommerce platforms, marketing signals, etc.)

🏖️ Benefits

• None specified