Global Women in Data Science(WiDS) termed as the Women’s March for analytics is the biggest event on the data science community calendar that showcases women in the field. This conference was founded by Margot Gerritsen, a Stanford faculty member and Director of Stanford's Institute for Computational and Mathematical Engineering (ICME) happens on March 5 at Stanford University in the heart of Silicon Valley.There are other sister conferences that happen across various cities in US and more than 50 countries. Last year approximately 75,000 people attended it and this year they are expecting 100,000 attendees for the largest analytics conference. The conference is attended by professionals from the industry, academia students and students who are soon to be sought-after data science hires.
(Source https://www.forbes.com/sites/metabrown/2018/03/01/100000-people-will-attend-global-women-in-data-science-conference/#6d5c14086d9a )
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It is really a difficult task to find someone who is experienced in both in law and data science, there are few traits which make both great lawyers and great data scientists. For any law firm looking to hire a data scientist, these are the 4 traits of a great data scientist -
i) Persistence - Look for data scientists who have a dogged dedication to pursue the truth, even in the face of adversity.
ii) Creativity - Hire a data scientist who is always willing to try new approaches.
iii) He/She should be a technical and quantitative chop.
iv) Must have a inquisitive nature.
(Source : https://www.law.com/2018/03/07/building-a-law-firm-data-science-team-4-traits-of-a-great-data-scientist/?slreturn=20180209130233 )
Whenever a new prospective client comes to you saying that they need to hire a data scientist then these are the foremost important 4 questions that you need to ask your client -
1. How much data do you have?
2.What do you imagine this data scientist will do once hired?
3. What support networks are available to your data scientist(s)?
4. Does your organization have established key performance indicators (KPIs) and regular business intelligence reporting?
The process of hiring and retaining good data scientists is expensive and competitive, however, being conscientious and smart on who , when and how to hire can reduce the pain and cost.
(Source : https://www.entrepreneur.com/article/310505 )
Data scientists are in great demand by organizations across the world, however in Indonesia, the huge demand is met with by a shortage of talent.Ainun Najib, the head of data at Malaysian ride-hailing company Grab said the shortage of talent is because of the education system which is not designed to produce data scientists. This is not just the case with Indonesia alone but even other countries face similar situation since data science is a new field and still growing. Data scientists need to master 3 different skills - have an in-depth understanding of consumers and marketing, analytical thinking related to math and stats, and technical ability , in particular programming.
(Source : http://www.thejakartapost.com/life/2018/03/25/data-scientists-in-high-demand-amid-talent-shortage.html )
The demand for analytical skills is increasing continuously and this trend is likely to continue with the number of data scientists far outweighing the number of graduates produced.Professor Riaan de Jongh, director of the Centre for Business Mathematics and Informatics at North-West University says that -”For every 66 data science jobs available, there are only 33 skilled data scientists.” According to Gartner, the demand for data scientists is growing three times that of statisticians and business intelligence analysts. The report further adds that more than 40% of data science tasks will be automated by 2020 which will result in enhanced productivity of citizen data scientists.
(Source : https://www.itweb.co.za/content/KBpdgvpPZ9yvLEew )
If you are a data scientist, don’t presume that you will be hired by the best investment bank. Shary Mudassir, a managing director in global equities trading at RBC Capital Markets said - “It’s hard to attract and retain highly capable AI talent – if you get 100 applicants, then 90 of them are not really data scientists, and if you get 10 average data scientists, they won’t be as effective as one really good data scientist.The 99th-percentile [employee] will add 80% of the value for the entire team.” Several AI professionals and data scientists have entered into the research environment but that is not the kind of experience RBC Capital Markets is looking for. Everything at RBC is an integral part of large operational system and not an R&D shop. The juniors that they hire are much driven by their work play out in the real world and not just focussed on research but eagerly looking to enhance the field of AI.
(Source : https://news.efinancialcareers.com/us-en/311390/data-science-jobs-banking )