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Pandora/SiriusXM is currently looking for Summer 2020 interns on our Radio & Music Informatics team. We're looking for candidates with a strong background in recommender systems, machine learning, music generation, or natural language processing.

If you're looking to work on Audio Entertainment (including Music, Podcasts, News, etc) at scale we might have just what you're looking for. Our service spins music to over 100 million monthly active listeners and we have collected over 90 billion thumbs. On the content-based side we're working with millions of songs labeled by expert musicologists on up to 450 musical characteristics, and access to dozens of millions of music tracks from our catalog.

Selected candidates will be working with members of our research team, led by Òscar Celma. Interns are well compensated and our office is located in Oakland, California in the beautiful San Francisco Bay Area.

You can find more about our internship program and apply here:
http://www.pandora.com/careers/roadcrew
https://recruiting.adp.com/srccar/public/nghome.guid?c=1147611&d=ExternalCareerSite&prc=RMPOD3&r=5000541409506

Requirements:
- PhD candidate in CS/EE/Statistics/Math or other technical field

Pluses:
- Strong publication record in machine learning, recommender systems, natural language processing, and/or music information retrieval
- Ability to prototype and develop custom algorithms
- Knowledge of recommender systems
- Proficiency in Python/Scala/Java
- Experience in Spark/Hadoop/GCP

❇️ @AI_Python_EN



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Pandora/SiriusXM is currently looking for Summer 2020 interns on our Radio & Music Informatics team. We're looking for candidates with a strong background in recommender systems, machine learning, music generation, or natural language processing.

If you're looking to work on Audio Entertainment (including Music, Podcasts, News, etc) at scale we might have just what you're looking for. Our service spins music to over 100 million monthly active listeners and we have collected over 90 billion thumbs. On the content-based side we're working with millions of songs labeled by expert musicologists on up to 450 musical characteristics, and access to dozens of millions of music tracks from our catalog.

Selected candidates will be working with members of our research team, led by Òscar Celma. Interns are well compensated and our office is located in Oakland, California in the beautiful San Francisco Bay Area.

You can find more about our internship program and apply here:
http://www.pandora.com/careers/roadcrew
https://recruiting.adp.com/srccar/public/nghome.guid?c=1147611&d=ExternalCareerSite&prc=RMPOD3&r=5000541409506

Requirements:
- PhD candidate in CS/EE/Statistics/Math or other technical field

Pluses:
- Strong publication record in machine learning, recommender systems, natural language processing, and/or music information retrieval
- Ability to prototype and develop custom algorithms
- Knowledge of recommender systems
- Proficiency in Python/Scala/Java
- Experience in Spark/Hadoop/GCP

❇️ @AI_Python_EN

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That growth environment will include rising inflation and interest rates. Those upward shifts naturally accompany healthy growth periods as the demand for resources, products and services rise. Importantly, the Federal Reserve has laid out the rationale for not interfering with that natural growth transition.It's not exactly a fad, but there is a widespread willingness to pay up for a growth story. Classic fundamental analysis takes a back seat. Even negative earnings are ignored. In fact, positive earnings seem to be a limiting measure, producing the question, "Is that all you've got?" The preference is a vision of untold riches when the exciting story plays out as expected.

At a time when the Indian stock market is peaking and has rallied immensely compared to global markets, there are companies that have not performed in the last 10 years. These are definitely a minor portion of the market considering there are hundreds of stocks that have turned multibagger since 2020. What went wrong with these stocks? Reasons vary from corporate governance, sectoral weakness, company specific and so on. But the more important question is, are these stocks worth buying?

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