"Should have been business model rather than mode"
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John Calhoon commented on Matt Reaney's blog post Academia to Industry: Applying Your PhD In BusinessJohn Calhoon commented on Matt Reaney's blog post Academia to Industry: Applying Your PhD In Business"A lot of good points in this article. Some additional things to consider include:
What is the company's business mode? How do they make money?
Who are the company's customers?
Who are the company's competitors?
What is the…"
Matt Reaney posted a blog postAcademia to Industry: Applying Your PhD In Business
After years of working on your PhD and being in academia, transitioning into a Data Science career can be a culture shock. It’s important to understand how the roles you are wanting to apply to vary; what industry is it in? What are the main focus of the projects? Who will you be working alongside? What are the end goals the team would be working on achieving? Does your chosen industry have anything to do with your PhD and academic research? ‘Data Scientist’ is becoming an ever-ambiguous term…See More
Matt Reaney's blog post was featuredAcademia to Industry: Applying Your PhD In Business
After years of working on your PhD and being in academia, transitioning into a Data Science career can be a culture shock. It’s important to understand how the roles you are wanting to apply to vary; what industry is it in? What are the main focus of the projects? Who will you be working alongside? What are the end goals the team would be working on achieving? Does your chosen industry have anything to do with your PhD and academic research? ‘Data Scientist’ is becoming an ever-ambiguous term…See More
Matt Reaney liked William Vorhies's blog post The Difference Between Managing Large and Small Data Science TeamsMatt Reaney liked Vincent Granville's blog post Two More Math Problems: Continued Fractions, Nested Square Roots, Digits of PiMatt Reaney liked Vincent Granville's blog post Two More Math Problems: Continued Fractions, Nested Square Roots, Digits of PiMatt Reaney posted a blog postWhy You Need To Keep Learning In Data Science
You’ve made it! The years of hard work and gaining experience in your field has finally paid off. You’re a Data Scientist! You’re a part of an innovative, forward-thinking team working on exciting, world-changing projects. You’ve got a great salary and tasty benefits package, flexible working and not an uncomfortable suit and tie in sight. Time to put down the books and enjoy the ride? Absolutely not! Quite the opposite in fact, and here is why. The field of Data Science is a vast landscape…See More
Matt Reaney posted a blog postAre You Ready To Become A Chief Data Scientist?
You know who you are. A high-calibre machine learning magician, a well-versed wrangler of data... but you want a bit more from your role. That may be progression, more money or the chance to work on new, more exciting projects, but where do you go from here? Many companies are looking to increase investment in data science departments and looking for leaders to build out new teams to do this. But before you take the plunge into the C-level, weigh up what this role entails and how much it will…See More
Matt Reaney's blog post was featuredAre You Ready To Become A Chief Data Scientist?
You know who you are. A high-calibre machine learning magician, a well-versed wrangler of data... but you want a bit more from your role. That may be progression, more money or the chance to work on new, more exciting projects, but where do you go from here? Many companies are looking to increase investment in data science departments and looking for leaders to build out new teams to do this. But before you take the plunge into the C-level, weigh up what this role entails and how much it will…See More
Rosaria Silipo commented on Matt Reaney's blog post Creativity Is Crucial In Data Science"Very nicely said! Our job is not just an automatic number crunching. The more creativity you use, the more surprising the results are. I always say: "We have the technology. We need to add the imagination". And creativity ranges from the…"
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Matt Reaney's Blog
Academia to Industry: Applying Your PhD In Business
Posted on July 24, 2018 at 6:17am 2 Comments 0 Likes
After years of working on your PhD and being in academia, transitioning into a Data Science career can be a culture shock.
It’s important to understand how the roles you are wanting to apply to vary; what industry is it in? What are the main focus of the projects? Who will you be working alongside? What are the end goals the team would be working on achieving? Does your chosen industry have anything to do with your PhD and academic research?
‘Data Scientist’…
Continue Are You Ready To Become A Chief Data Scientist?
Posted on May 23, 2018 at 1:00am 0 Comments 1 Like
You know who you are. A high-calibre machine learning magician, a well-versed wrangler of data... but you want a bit more from your role. That may be progression, more money or the chance to work on new, more exciting projects, but where do you go from here?
Many companies are looking to increase investment in data science departments and looking for leaders to build out new teams to do this. But before you take the plunge into the C-level, weigh up what this role entails and…
Continue 5 Common Non-Technical Interview Questions... and Answers
Posted on March 20, 2018 at 6:30am 0 Comments 2 Likes
It can be difficult to know what to expect when going for an interview. Data Science interviews will require candidates to answer technical questions, and often take on technical exercises depending on the company and role you’re going for.
But often overlooked is the talk about soft skills, such as communication skills business savvy, creativity and impact your work has had in the past.
Here is a selection of non-technical questions you could get asked to help you prepare for…
Continue 5 Questions To Prepare You For Your Next Data Science Interview
Posted on March 13, 2018 at 4:30am 0 Comments 0 Likes
Sat across from the interviewer for your dream job, you may start to feel the pressure. A sure-fire way to quash the interview jitters is to prepare as much as possible. Typically, you can segment the types of questions you’ll get asked in a data science interview; things such as statistics, programming and technical ability, business acumen, and culture fit assessment. Studying up on these will help you prepare as best you can.
Here are some examples of what you…
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