Data Analytics Engineer

Position Overview

Advantest is seeking a versatile Senior Data Analytics Engineer to design, develop, and deploy data solutions that bridge infrastructure, analytics, and machine learning. In this individual contributor role, you will own the full lifecycle of data projects—from building scalable pipelines to developing predictive models—that empower semiconductor R&D, test, and operations teams.

This role is ideal for a hands-on engineer who thrives in a fast-paced environment and is comfortable wearing multiple hats, from architecting data workflows to modeling complex datasets and integrating ML models into production.

Key Responsibilities

• Design and optimize ETL/ELT pipelines to process large-scale, high-velocity semiconductor data (e.g., fab telemetry, test results).
• Build and maintain scalable data platforms using modern tools across cloud and on-prem environments.
• Ensure data quality, security, and accessibility for downstream analytics and ML use cases.
• Partner with data scientists to operationalize predictive models (e.g., reliability prediction, anomaly detection, classification) into production pipelines.
• Develop and maintain ML infrastructure (MLOps) for model monitoring, retraining, and versioning.
• Perform feature engineering, statistical analysis, and domain-specific modeling (e.g., time-series analysis for semiconductor manufacturing).
• Collaborate with semiconductor engineers to translate domain challenges into data-driven solutions.
• Experiment with emerging tools (e.g., LLMs, causal inference) to innovate on analytics capabilities while balancing business impact.
• Communicate technical findings to non-technical stakeholders through dashboards or strategic recommendations.

Required Qualifications

• Education: M.S./Ph. D in Computer Science, Data Science, Engineering, or a quantitative field.
• Experience Required: 5+ years of hands-on experience in at least two areas among data engineering (ETL/ELT, pipeline development, cloud platforms), ML engineering (MLOps, model deployment, production ML systems), and advanced analytics (predictive modeling, statistical analysis, domain-specific problem-solving).
• Qualifications: Proficiency in Python, ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), Pandas/Dask/Polars, and NumPy; experience with API development (FastAPI); familiarity with ML deployment tools (e.g., Docker, Kubernetes) and Linux; and knowledge of dashboarding tools (e.g., Grafana, Power BI, Dash, Tableau) and DevOps tools (e.g., git, GitHub, Jenkins).

Preferred Qualifications

• Knowledge of semiconductor manufacturing and testing processes.
• Experience with LLM-based tools and agentic solutions (e.g., prompt engineering, workflow automation, decision support systems).
• Experience with causal inference techniques (e.g., identifying root causes of manufacturing defects, optimizing process parameters).
• Familiarity with cloud platforms (AWS/Azure/Google Cloud) and cloud orchestration tools (e.g., Terraform).

Benefits & Perks

• Benefits: Global Bonus Program – Performance-based bonuses paid twice yearly.
• Benefits: 401(k) Plan – Pre-tax retirement savings with company match.
• Benefits: Medical, Dental & Vision – Multiple plan options including HMO, PPO, and HSA.
• Benefits: Income Protection – Life, disability, and accident insurance at no cost.
• Benefits: Flexible Spending Accounts – Healthcare and dependent care options.
• Benefits: Employee Assistance Program – Free support for personal and work-related issues.
• Benefits: Flexible Time Off – Accrual starts at hire, increases with service.
• Benefits: Paid Holidays – 13 company holidays annually.