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Senior Data Scientist - Manufacturing Data (US)

Gauss LabsPalo Alto, CA

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Overview

Schedule
Full-time
Education
Engineering (PE)
Career level
Senior-level
Remote
On-site

Job Description

As a Data Scientist, you will play a pivotal role in aligning our AI solutions with the unique needs of our manufacturing clients. Your primary responsibility will be to lead the development of state-of-the-art AI applications that tackle complex industry challenges, driving innovation and enhancing productivity.

We are seeking an experienced data scientist capable of extracting valuable insights from manufacturing data. Your tasks will include mining, interpreting, and analyzing customer data to discover hidden opportunities and fully leverage its potential. Also, your role will involve direct interaction with customers to grasp their challenges and to understand their unique data characteristics. By closely engaging with customers, you will develop tailored data models and tools to meet their specific needs. Additionally, you will collaborate with our cross-functional teams to conceive, design, and develop innovative AI products for manufacturing by identifying new product features based on the understanding of customer data.

Join a team of passionate innovators dedicated to revolutionizing the future of manufacturing. Take the lead in pioneering cutting-edge AI initiatives that directly impact real-world outcomes. Collaborate with a diverse and talented group of experts where your ideas will be highly valued, and your contributions will drive Gauss Labs towards becoming the global leader in industrial AI innovation.

Responsibilities

  • Design and implement customized AI solutions for manufacturing.
  • Analyze manufacturing data to uncover opportunities and develop AI models.
  • Collaborate with customers to understand their requirements and deliver clear, data-driven solutions.
  • Work closely with our internal teams to ensure solutions are feasible, scalable, and aligned with product strategy.
  • Present findings to both technical and non-technical stakeholders.

Basic Qualifications

  • BS/MS in Engineering, Science, or a related field.
  • 3+ years of experience leading AI or data science projects in the semiconductor industry or another manufacturing field.
  • Strong problem-solving skills and customer-focused mindset.
  • Proficiency in data science tools: Python and SQL.
  • Ability to work independently and as part of a team.
  • Travel domestically to customer sites as needed (up to 20% of working hours).

Preferred Qualifications

  • MS in Computer Science, Data Science, or related field.
  • Experience in predictive modeling and cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Excellent communication skills, with the ability to simplify complex technical concepts.
[Interview Process]
Application review- Phone interview- Virtual onsite interview- VP interview & Core Value interview- CEO interview

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FAQs About Senior Data Scientist - Manufacturing Data (US) Jobs at Gauss Labs

What is the work location for this position at Gauss Labs?
This job at Gauss Labs is located in Palo Alto, CA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Gauss Labs?
Employer has not shared pay details for this role.
What employment applies to this position at Gauss Labs?
Gauss Labs lists this role as a Full-time position.
What experience level is required for this role at Gauss Labs?
Gauss Labs is looking for a candidate with "Senior-level" experience level.
What education level is required for this job?
The education requirement for this position is Engineering (PE). Candidates with relevant qualifications or equivalent experience may also be considered.
What is the process to apply for this position at Gauss Labs?
You can apply for this role at Gauss Labs either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.