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Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

Blue river technology Salaries by Position

<h3>Job Description</h3><div>Job Description<div>Title and Location: Sr. Machine Learning Engineer in Santa Clara, CA. Job Responsibilities<ul><li>Implement deep-learning-based classification systems for construction.</li><li>Explore and develop new methods for improving detection performance and improving the runtime of inference.</li><li>Work with internal customers to develop machine learning pipelines for computer vision-based classification tasks.</li><li>Help to architect and develop the data pipeline and platform supporting machine learning.</li><li>May work remotely; periodic time in office required; must live within commuting distance of the office.</li></ul>Qualifications<ul><li>Master's degree in Machine Learning and Robotics or related field or foreign academic equivalent</li><li>2 years of related experience</li><li>Required skills: Research and develop Deep Learning models for depth estimation, object classification, and scene segmentation for large-scale datasets (2 years)</li><li>Experience working with Python and Deep learning frameworks including Pytorch, TensorRT, Pandas (2 years)</li><li>Experience working with model hyperparameter optimization and loss function tuning to improve performance (2 years)</li><li>Comfortable working with large-scale GPU cloud computing/infrastructure for training deep learning models (2 years)</li><li>Has explored methods (new model architectures, quantization, ablation study) to optimize model inference time on embedded devices (2 years)</li><li>Architect and develop data processing and annotation pipelines for training models (2 years)</li><li>Formulate ML metrics and evaluate models for robotics tasks (2 years)</li></ul>Full time. $154,000 - $275,000/year. Please visit https://bluerivertechnology.com/join-us/ to apply. #LI-DNI</div></div>

Title and Location : Sr. Machine LearningEngineer in Santa Clara, CA.

Job Responsibilities

Implement deep-learning-based classification systems for construction.

Explore and develop new methods for improving detection performance and improving the runtime of inference.

Work with internal customers to develop machine learning pipelines for computer vision-based classification tasks.

Help to architect and develop the data pipeline and platform supporting machine learning.

May work remotely; periodic time in office required; must live within commuting distance of the office.

Qualifications

Master's degree in Machine Learning and Robotics or related field or foreign academic equivalent

2 years of related experience

Required skills: Research and develop Deep Learning models for depth estimation, object classification, and scene segmentation for large-scale datasets (2 years)

Experience working with Python and Deep learning frameworks including Pytorch, TensorRT, Pandas (2 years)

Experience working with model hyperparameter optimization and loss function tuning to improve performance (2 years)

Comfortable working with large-scale GPU cloud computing/infrastructure for training deep learning models (2 years)

Has explored methods (new model architectures, quantization, ablation study) to optimize model inference time on embedded devices (2 years)

Architect and develop data processing and annotation pipelines for training models (2 years)

Formulate ML metrics and evaluate models for robotics tasks (2 years)

Full time. $154,000 - $275,000/year. Please visit https://bluerivertechnology.com/join-us/ to apply.

#LI-DNI

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Blue river technology Interview Questions

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Blue river technology Interview Questions

Blue river technology Salaries by Position

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