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Trainee Machine Learning Neuroscience Jobs (NOW HIRING)

Tacit

Computational Neuroscientist

San Francisco, CA · On-site

$160K - $180K/yr

PhD in neuroscience, biomedical engineering, machine learning, computer science, or related fields (or equivalent industry experience). * Fluency in Python and PyTorch. * Ability to collaborate ...

Service Wire

Machine Operator Trainee

Culloden, WV · On-site

$15K/yr

Trainees will gain experience in equipment setup, machine operation, troubleshooting, wire quality monitoring, material handling, and production documentation while learning and applying all company ...

Service Wire

Machine Operator Trainee

Culloden, WV

$15K/yr

Trainees will gain experience in equipment setup, machine operation, troubleshooting, wire quality monitoring, material handling, and production documentation while learning and applying all company ...

Service Wire

Machine Operator Trainee

Culloden, WV

$15K/yr

Trainees will gain experience in equipment setup, machine operation, troubleshooting, wire quality monitoring, material handling, and production documentation while learning and applying all company ...

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How much do trainee machine learning neuroscience jobs pay per year?

As of Jun 3, 2026, the average yearly pay for trainee machine learning neuroscience in the United States is $43,530.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,000.00 and $51,000.00 per year, depending on experience, location, and employer.
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Business Data Scientist, Applied Machine Learning, GCS

Google

Manhattan, NY • On-site

Full-time

Posted 27 days ago

Google rating

8.8

Company rating: 8.8 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

31st of 185 rated software companies

Job description

Job Summary:
Google is a leading technology company, and they are seeking a Business Data Scientist to join their GCS Data Science team. In this role, you will immerse yourself in data collection and analysis, develop machine learning models, and communicate insights to senior-level executives to drive business strategies.
Responsibilities:
• Design, develop, and validate robust causal inference models (e.g., Synthetic Control, Difference-in-Differences, Double Machine Learning) to isolate the incremental impact of GCS programs.
• Partner with business teams to design and execute A/B tests, defining the sample sizes, power analyses, and success metrics required for valid results.
• Stay current with the latest academic research in Causal ML and Econometrics, proactively prototyping new methods to improve the precision of our impact estimates.
• Distill highly technical methodologies into clear, prescriptive business narratives for non-technical executive audiences.
• Establish comprehensive monitoring systems to track model performance, detect data drift, and ensure the ongoing accuracy of deployed measurement frameworks.
Qualifications:
Required:
• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred:
• PhD in a quantitative discipline such as Computer Science, Engineering, Economics, Statistics, Mathematics, Physics, Neuroscience, or equivalent practical experience.
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
• Experience in driving a project from an experimental idea to a proof-of-concept to a launched product feature.
• Experience in publications and working with technologies.
Company:
Google specializes in internet-related services and products, including search, advertising, and software. It is a sub-organization of Alphabet. Founded in 1998, the company is headquartered in Mountain View, USA, with a team of 10001+ employees. The company is currently Late Stage.

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Hours and flexibility

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