Applied Data Scientist

For C2C H1B only Job Title: Senior Applied Data Scientist Location: Irvine, CA Duration: Long Term Job Description: Experienced Required: • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical field. • 6+ years of hands-on experience in applied data science, machine learning, or AI system development. • 3+ years of experience building and deploying ML/AI models integrated with production software (C++, Python, Go or related language). • Proven experience working with AWS Cloud for model training, data pipelines, and deployment (SageMaker, Lambda, Glue, ECS/EKS, Redshift, S3). • Practical experience developing visualizations and dashboards using Amazon QuickSight or similar BI tools. • Familiarity with containerization (Docker) and orchestration (ECS/EKS) for scalable, fault-tolerant deployments. • Understanding of MLOps principles, CI/CD pipelines, and model monitoring practices. • Data Science or AWS Cloud certification preferred. Job Summary • Lead the design and development of applied ML and AI solutions that directly support Panasonic’s inflight system platforms. • Build and deploy scalable models that integrate with core applications written in C++, Python, and Go, supporting real-time decision-making across connectivity, content, and operational services. • Develop and operationalize predictive, prescriptive, and optimization models using AWS services such as SageMaker, Lambda, Glue, ECS/EKS, Redshift, and S3. • Use Amazon QuickSight and similar tools to visualize model outcomes, performance trends, and business insights. • Lead applied research and experimentation with Panasonic’s operational data to design lightweight Business Growth Models (BGMs) and other analytical frameworks & strategies. • Collaborate closely with data science, data engineering, and product teams to bring scientific models into production, ensuring stability, scalability, and measurable business impact. • Explore and apply emerging ML and optimization methods, containerization (Docker, ECS, EKS), and MLOps best practices to improve model reliability and automation. • Stay current with developments in applied AI and embedded systems, evaluating opportunities to strengthen Panasonic’s data-driven aviation ecosystem. Required Skills • Strong software-engineering foundation; proficiency in Python and at least one compiled language (C++, Python, or Go). • Ability to integrate ML models directly into core software systems using APIs, microservices, or embedded components. • Deep understanding of machine learning, statistical modeling, and optimization techniques for operational use cases. • Experience designing and automating end-to-end ML pipelines using AWS and modern MLOps tooling. • Knowledge of ETL, data wrangling, and feature engineering for large-scale structured and unstructured data. • Experience developing containerized model services and working with orchestration frameworks for production scaling. • Proficiency with QuickSight or similar tools to visualize data trends, model diagnostics, and KPI tracking. • Familiarity with data governance, quality, and metadata management practices. • Strong analytical and communication skills; able to convey technical concepts clearly to engineering and business teams. • Experience mentoring peers and driving adoption of modern data science and software practices. Major Responsibilities • Design, develop, and deploy ML and AI models integrated with Panasonic’s core software stack (C++, Java, Go). • Build and maintain containerized, production-ready pipelines and inference services using AWS Cloud. • Collaborate with software and data engineering teams to design APIs and integration patterns for embedding ML capabilities within inflight and airside applications. • Lead applied research on operational data to develop lightweight Business Growth Models (BGMs) that optimize inventory and ad placement strategies. • Apply advanced ML and statistical methods to improve operational efficiency and passenger experience. • Establish and maintain MLOps best practices for continuous integration, model retraining, and monitoring. • Partner with product managers to define measurable success criteria and ensure deployed models deliver business value. • Mentor junior scientists and engineers on applied ML development, testing, and deployment. • Stay informed on emerging ML/AI frameworks and identify opportunities to enhance Panasonic’s data-driven capabilities.