Data Analytics Engineer

Position Overview:

As a Data Analytics Engineer, you will be designing, deploying, and improving applications using advanced models, statistics, and logic. You will collaborate with various teams to translate business objectives into automated solutions using diverse datasets including time series data, high-dimensional data, images and more. You will also focus on staying up-to-date with the latest advancements in AI and machine learning, and experimenting with new techniques to drive innovation in the organization's data science practices.

Key Responsibilities:

• Collaboration with Cross-Functional Teams: Work closely with manufacturing engineers, process engineers, and operations teams to ensure analytics solutions are aligned with business needs.
• Data Integration & Engineering: Identify, integrate, or create data sources to support analytics applications.
• Data Modeling & Analysis: Create models to identify trends, correlations, and patterns that drive production efficiency and quality improvements.
• Workflow Automation: Design, develop, implement, and continuously improve automated processes and visualizations to enhance personnel efficiency.
• Organizational Growth: Attend conferences, consortium, and coalition meetings on Smart Manufacturing -related topics to bring in best practices to Polar.

Typical Projects:

• Manufacturing Productivity: Implement Digital Twins and predictive models to improve throughput, OEE, while reducing cycle times and cost.
• Manufacturing Quality: Create models and algorithms to improve process capability, process control (APC and FDC), line yield, die yield, reliability, and reduce defect rates.
• Manufacturing Technology: Streamline technology development, integration, and improve Product Lifecycles by using advanced models, simulation, and Digital Twins.

Required Qualifications:

• Education: Bachelor’s degree in Data Science, Engineering, Computer Science, or a related field.
• Experience:
  • 5+ years of experience in data analytics, data science, or data engineering, ideally within the semiconductor manufacturing industry.
  • Used cloud computing services to store, process, and query data, Azure is preferred.
  • Designed, developed and deployed machine learning models and visualizations to solve manufacturing problems.
• Technical Skills:
  • Strong understanding of various machine learning models and their effective application to diverse datasets.
  • Experienced with statistical software, JMP is preferred.
  • Experienced with scripting languages, Python (NumPy, Pandas, OpenCV), JSL, and Javascript are preferred.
  • Experienced with programming languages, C# on .NET is preferred.
  • Experienced with SQL, Oracle is a plus.
  • Proficient with signal processing, transformations, and filtering techniques.
  • Comfortable with model performance evaluation and comparison.
  • Comfortable with statistical hypothesis tests.
  • Comfortable with random distributions and simulation techniques.
  • Comfortable with source control, Git is preferred.
• Soft Skills:
  • Strong analytical and problem-solving abilities.
  • Strong attention to detail and organizational skills, particularly in documenting code and applications.
  • Aware of the latest trends in data analytics applicable to the semiconductor industry.

Preferred Qualifications:

• Familiarity with the semiconductor manufacturing ecosystem, including industry standards, processing, performance metrics, Lean Six Sigma Tools, and Smart Manufacturing methodologies.
• Experienced with Linux, shell scripting, cron jobs, and troubleshooting.
• Experienced with Python machine learning libraries, such as Pytorch, TensorFlow, scikit-learn, etc.
• Familiarity with computer vision, LLMs, Digital Twins, and other advanced technologies.

The estimated base salary range for the position is $98,000- $122,000.  The pay offered is based on many factors including, but not limited to, relevant education, job-related experience, skills and level of the position.

• Full-time employees will be eligible to receive the following benefits and additional compensation:

  • Medical, Dental and Vision Insurance

  • Paid Time Off starting the first day

  • 401k including a generous company match

  • Tuition assistance

  • Disability and life insurance

  • Legal and ID theft insurance

  • Employee Assistance Program

  • Annual Incentive Program (Bonus)