Data Analytics Engineer

We are seeking a highly skilled and innovative Data Analytics Engineer to lead the design, development, and deployment of advanced analytics solutions that drive data-informed decision-making across semiconductor R&D, test, and operations. You will work closely with engineering, product, and partner teams to build scalable data pipelines, architect machine learning infrastructure, and derive actionable insights from complex, high-volume datasets. This role blends engineering rigor, business strategy, and technical leadership to enable next-gen test solutions across the semiconductor lifecycle.

We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

Skills and Requirements

• M.S. or Ph.D. in Computer Science, Data Science, or a related field.
• 5+ years of experience in data analytics or data engineering, including leadership roles.
• Proven experience building and deploying ML/AI systems (e.g., LSTM, GRU, CNN, XGBoost) in production environments.
• Hands-on expertise with modern big data tools and infrastructure: AWS, Docker, Kubernetes, PySpark, Airflow, SQL, Git.
• Solid understanding of statistical methods, time series forecasting, anomaly detection, and causal inference techniques.
• Strong communication skills with experience translating technical outcomes into business strategy.

Tools & Technologies

• Languages: Python, SQL, C++, R, Java
• Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, FastAPI
• Data Platforms: AWS, Azure, Snowflake, Hadoop, Spark
• Visualization: Tableau, PowerBI, Matplotlib, Seaborn
• DevOps: Docker, Kubernetes, GitHub Actions, MLFlow