Sr. Data Scientist, Hardware Reliability (Starlink Product)

Required Skills

Responsibilities

• Build and maintain critical data science infrastructure, tools, processes, and custom software to objectively assess the performance and reliability of Starlink customer hardware
• Lead technical data-driven investigations with tight timelines by diving into isolated or fleet-wide performance or reliability issues affecting our customers and present findings to executives
• Apply data science and statistical inference techniques to analyze data and build models that help improve customer experience and drive business growth
• Build software systems that ingest, transform, store, and combine data from multiple sources
• Create custom datasets, analyses, and analytics tools that will be used by internal teams and stakeholders to monitor, analyze, and impact business outcomes
• Consistently contribute effort, leadership, and creative thinking to solving complex problems in a collaborative fashion under tight deadlines
• Build relationships and collaborate across disciplines including engineering, production, test, inventory, quality, supply chain, and customer experience to drive positive business outcomes
• Bachelor’s degree in computer science or data science
• 3+ years of professional experience in data or software engineering in Python, SQL, or Bash scripting
• 2+ years of professional experience in data science and machine learning fundamentals (regression, classification, clustering, anomaly detection, natural language processing)
• Master’s degree in computer science, data science, mathematics, or other STEM discipline
• 6+ years of professional experience in data or software engineering, with strong proficiency in Python, SQL, Bash scripting, and familiarity with at least one additional programming language (e.g., R, Java, Scala, C++)
• 5+ years of professional experience in data science and machine learning fundamentals (regression, classification, clustering, anomaly detection, natural language processing)
• Experience building production-level predictive models, machine learning solutions, and analytics pipelines
• Strong software engineering skills; ability to write clean, efficient, and robust code with a foundation in software development best-practices; ability to contribute to internal code repositories and production services
• Deep expertise cleaning, aggregating, analyzing and automating large, industry-complex datasets
• Strong in data engineering fundamentals – relational databases, data pipeline development and orchestration, and data science-focused cloud development
• Strong analytical skills: Statistical analysis, data visualization, and quantitative reasoning
• Excellent written and verbal communication skills, ability to make presentations to engineers, team members, internal customers, and management