System and Analog Data Scientist (Semiconductor)

Location: Haifa, Israel

Company

Develops complex system-on-chip (SoC) and analog circuit solutions.

What you will do

• Develop data collection, cleaning, and transformation pipelines for system and analog design and test data.
• Apply statistical analysis, machine learning, and deep learning to identify patterns, anomalies, and correlations in large datasets.
• Create predictive models for circuit performance, reliability, and yield to inform design decisions and reduce design iterations.
• Design and execute experiments to validate models and measure the impact of data-driven insights on product development.
• Collaborate with design, verification, and test engineering teams to integrate data science solutions into existing workflows.
• Present analytical findings through clear visualizations and reports to technical and non-technical stakeholders.

Requirements

• Bachelor’s, master’s, or doctoral degree in Electrical Engineering, Computer Science, Data Science, Statistics, or a related quantitative field.
• 3+ years of experience applying data science and machine learning techniques to engineering problems, preferably in the semiconductor industry.
• Strong programming skills in Python and R, including Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Experience with statistical modeling, regression, classification, clustering, time-series analysis, and deep learning architectures.
• Understanding of semiconductor design flows, analog circuit fundamentals, and system-level architectures.
• Strong problem-solving, communication, collaboration, and presentation skills.

Nice to have

• Familiarity with data warehousing, SQL, and big data technologies such as Spark or Hadoop.

Culture & Benefits

• Regular full-time employment.
• Shift 1 schedule in Israel.
• Work alongside design, verification, and test engineering teams.