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X-WR-CALNAME;VALUE=TEXT:Careers in Data Science: Transitioning from Academia to the Technology Industry
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SUMMARY:Careers in Data Science: Transitioning from Academia to the Technology Industry
DESCRIPTION:<p><span style="font-size: large; font-family: times new roman,times;">Speaker: Kevin Mercurio (Harvard Physics PhD '14), Data Scientist and Program Director, Insight Data Science</span><span style="font-size: large; font-family: times new roman,times;"></span><br><br><span style="font-size: large; font-family: times new roman,times;">The Harvard Physics Department invites you to a question &amp; answer seminar with Kevin Mercurio, a Harvard Physics alumnus and co-director at Insight Data Science in New York City. Insight Data Science is a tech-education startup with years of experience helping PhDs and Postdocs move into data-related careers, and Kevin will share his experiences and advice learned while helping many Insight Fellows make transitions from academia to their data science careers.</span><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">Silicon Valley technology companies like LinkedIn, Facebook, Square, Netflix and various startups, as well as New York companies such as Bloomberg, Flatiron Health, The New York Times, and Memorial Sloan Kettering Cancer Center are all hiring PhDs from quantitative fields to help them create actionable insights from the terabytes of data that they collect every day. While the amount of data these companies are producing and storing is growing exponentially, there is a severe shortage of top talent to organize this data and extract valuable insights from it through analysis.</span><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">Kevin will provide an introduction to data science careers and share stories of scientists who have transitioned from academia to the tech industry, including 500 Insight Fellows (a number of whom, like Kevin, are also alums of Harvard's PhD programs in physics, math, and related fields) who are now working as data scientists and data engineers at top data-driven companies. This will be followed by a Q&amp;A session.</span><br><br><span style="font-size: large; font-family: times new roman,times;">Complimentary drinks and snacks will be served.</span></p><p><span style="font-family: times new roman,times;">T<span style="font-size: large;">o register, go </span></span><a href="https://harvard.az1.qualtrics.com/jfe/form/SV_cHBkihyYKZwpXCJ" target="_blank" data-url="https://harvard.az1.qualtrics.com/jfe/form/SV_cHBkihyYKZwpXCJ"><span style="font-family: times new roman,times;"><span style="font-size: large;">here</span></span></a><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">You can learn more here:</span><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">- Insight Data Science Fellows Program (NYC, Silicon Valley, and Remote)</span><br><span style="font-size: large; font-family: times new roman,times;">http://insightdatascience.com</span><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">- Insight Data Engineering Fellows Program (NYC, Silicon Valley)</span><br><span style="font-size: large; font-family: times new roman,times;">http://insightdataengineering.com</span><br><span style="font-size: large; font-family: times new roman,times;"> </span><br><span style="font-size: large; font-family: times new roman,times;">- Insight Health Data Science Fellows Program (Boston)</span><br><span style="font-size: large; font-family: times new roman,times;">http://insighthealthdata.com</span></p>
LOCATION:Jefferson Laboratory 250, Cambridge
STATUS:CONFIRMED
DTSTART:20160317T160000Z
DTEND:20160317T170000Z
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