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Scientist

SiriusXM

Scientist

SiriusXM

Oakland, California

·

On-site

·

Full-time

·

1mo ago

Required skills

Python

Java

Scala

Machine Learning

Scientist - (employer: Sirius XM Radio LLC; job location: Oakland, CA) - Design, build, analyze and test machine learning recommender systems or music information retrieval systems for our algorithmic radio and recommendations products.

Improve upon existing capabilities of content understanding through analysis of audio data and metadata.

Conduct research to discover cutting-edge innovations in the music recognition technology industry.

Conduct scientific studies to uncover listener behavior on activity based music stations by observing music consumption.

Develop deep-learning-based music audio tagging models.

Develop novel techniques for algorithmic radio station generation, leveraging recommender systems and music understanding techniques and data.

Requirements: Master’s degree in Computer Science, Statistics, Computational Linguistics, or Music Technology, plus 1 year of experience in position offered or as Associate Scientist or Graduate Research Assistant in data science or music technology field.

All of the required experience must have included designing machine learning systems, recommender systems or music information retrieval system; programming in Python, Scala, or Java.

This role entails hybrid work, with time split between working in our Oakland, CA office and flexibility to telecommute from another U.S. location.

Salary: $168,500/year.

Apply online at www.siriusxm.com/careers.

Ref: P-2026-519. P-2026-519
Scientist - (employer: Sirius XM Radio LLC; job location: Oakland, CA) - Design, build, analyze and test machine learning recommender systems or music information retrieval systems for our algorithmic radio and recommendations products.

Improve upon existing capabilities of content understanding through analysis of audio data and metadata.

Conduct research to discover cutting-edge innovations in the music recognition technology industry.

Conduct scientific studies to uncover listener behavior on activity based music stations by observing music consumption.

Develop deep-learning-based music audio tagging models.

Develop novel techniques for algorithmic radio station generation, leveraging recommender systems and music understanding techniques and data.

Requirements: Master’s degree in Computer Science, Statistics, Computational Linguistics, or Music Technology, plus 1 year of experience in position offered or as Associate Scientist or Graduate Research Assistant in data science or music technology field.

All of the required experience must have included designing machine learning systems, recommender systems or music information retrieval system; programming in Python, Scala, or Java.

This role entails hybrid work, with time split between working in our Oakland, CA office and flexibility to telecommute from another U.S. location.

Salary: $168,500/year.

Apply online at www.siriusxm.com/careers.

Ref: P-2026-519.

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About SiriusXM

SiriusXM

SiriusXM

Public

SiriusXM Holdings Inc., commonly referred to as SiriusXM, is an American broadcasting corporation headquartered in Midtown Manhattan, New York City, that provides satellite radio and online radio services operating in the United States.

5,001-10,000

Employees

Midtown Manhattan

Headquarters

$6.5B

Valuation

Reviews

3.4

1 reviews

Work-life balance

3.0

Compensation

3.0

Culture

2.0

Career

2.0

Management

2.5

15%

Recommend to a friend

Cons

Poor interview process

Difficult behavioral interview questions

Salary Ranges

0 data points

Junior/L3

L3

Junior/L3 · Data Scientist II

0 reports

$131,667

total per year

Base

-

Stock

-

Bonus

-

$111,917

$151,417

Interview experience

5 interviews

Difficulty

2.4

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 80%

Negative 20%

Interview process

1

Application Review

2

Recruiter Screen

3

HireVue Video Interview

4

Technical and Behavioral Interview

5

Offer Decision

Common questions

Technical Knowledge

Behavioral/STAR

Coding/Algorithm

Past Experience