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So, What Does a Data Scientist do?


What a Data Scientist does in the music industry, and my thoughts on what a data scientist is. Presented at the March 2012 Data Science London meetup

What a Data Scientist does in the music industry, and my thoughts on what a data scientist is. Presented at the March 2012 Data Science London meetup

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  • Long infographic is long:
  • As of this writing there does not exist a "Data Scientist" entryin Wikipedia although there is one for
  • Microarray image from
  • Sewing a quilt probably doesn’t involve knitting


  • 1. So, What Does a Data Scientist do? A Data Scientist in the Music Industry Dr Jameel Syed March 2012
  • 2. Overview– Musicmetric CTO– InforSense founding member • PhD in Workflows for Life Sciences Analysis– Co-organiser Big Data London meetup
  • 3. Some questions...
  • 4. Music has moved online• The world has changed – Do you buy vinyl/tapes/CDs of music? – Do you buy music downloads? – Do you download illegal content from bittorrent? – Do you listen to music on YouTube? – Do you “like” bands on Facebook? – Do you subscribe to Spotify? – Do you listen on the radio to the weekly charts on a Sunday afternoon?• What’s happening online?
  • 5. How popular am I?
  • 6. Who are my fans?
  • 7. Where are my fans?
  • 8. What is the press saying?
  • 9. Who is popular?
  • 10. A Data Scientist in the Music Industry• Raw Data -> Derived Data -> Insight – Who is popular right now/in the immediate future? – What was the effect of appearing at a festival? – Which artists are (becoming) popular with listeners with certain demographics (in a region)?• Data processing, machine learning & statistical methods – Sentiment analysis – Named Entity Recognition – Ranking – Segmentation• One-offs – Infographics and microsites for events – Brand alignment via demographics – Music Hack Days• Product – Daily charts – Sentiment scoring web crawled reviews
  • 11. What is a Data Scientist?
  • 12. Have we been here before?• Statistician• Data Analyst• Quantitative analyst• Bioinformatician• Data Miner• Business Intelligence consultant• Computational physicst
  • 13. A Life Sciences digression...
  • 14. What’s new?• Data provides the opportunity – Old: Collect and store data presupposing how it will be used – New: Collect raw data & explore which derivations are interesting; integrating data from multiple online sources. – Big Data technology to cope with data volume• Programming is essential – APIs – Heterogeneous environment(s)• Method of presentation – Infographics – Interactive (web) applications – (Raw data)
  • 15. Data Scientist• “Jack of all trades” – “Hacker” mentality: learn new technology and approaches for a project on short notice – Creative self-starters – Work alongside other experts (data, domain, software engineering)
  • 16. A Data Scientist is good at knitting?• Not building from scratch, knitting together pre-existing parts• Data – Databases (relational/NoSQL) – Files – APIs• Algorithms – Open source libraries – Off the shelf tools• Compute – Linux – AWS?• Languages – Many, especially “scripting” languages