AI News, Will the Real Data Scientists Please Stand Up?
- On Friday, July 6, 2018
- By Read More
Will the Real Data Scientists Please Stand Up?
Perusing one list of skills, it seems that a data scientist must possess scripting and query language chops as well as business acumen in order find actionable insights in datasets.
And yet tens of other posts and job listings seek candidates to carry out fundamental research into machine learning algorithms and applications.
The range of candidates for so-called data science positions has grown to include computer scientists, mathematicians, and physicists as well as business school graduates, economists, and other social scientists.
Some positions seem to require mathematical maturity, others superior coding skills, and yet more are clearly looking for SQL jockeys, who can generate visualizations and insert them into powerpoint presentations.
While his body research spans the fields of machine learning, cognitive science, computational neuroscience and even psychology, he is a leading researcher who's invented many of the tools that now make it possible recognize objects in images, phonemes in audio, and patterns in text.
Generally, in the machine learning community, theorists are computer scientists, mathematicians, and statisticians, who primarily study algorithms that are provably efficient and provably correct, even if they must rely on unrealistically strong assumptions.
For these scientists, a single method whose behavior is understood is preferable to system which wins a Kaggle competition by cobbling together a gaggle of algorithms into an ensemble.
Tools of the Trade: Implementation is a significant part of machine learning work and machine learning scientists should have strong coding skills in both high and low-level languages, as well as the ability to rapidly prototype with existing machine learning frameworks like scikit-learn.
Data Miners What They Do: Unlike machine learning researchers who consider many abstract tasks, such as the active learning paradigm, and are often content to show state of the art performance on widely-studied datasets, data miners work on two types of problems.
They can be found at the traditional silicon valley powerhouses, but also in the health space, or mining data for companies that may not be primarily in the business of building high-tech solutions.
Computer and Information Research Scientists
Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology.
Computer and information research scientists typically do the following: Computer and information research scientists create and improve computer software and hardware.
Computer and information research scientists design new computer architecture that improves the performance and efficiency of computer hardware.
Their work often leads to technological advancements and efficiencies, such as better networking technology, faster computing speeds, and improved information security.
For example, they may create an algorithm to analyze a very large set of medical data in order to find new ways to treat diseases.
The new languages make software writing more efficient by improving an existing language, such as Java, or by making a specific aspect of programming, such as image processing, easier.
Research Scientist, Machine Learning Predictive Science
Current areas of investigation include application and development of novel computational approaches to unravel the mechanism of action of Celgene’s pipeline compounds and identify therapeutic targets, methods for integrative analysis of omics data, predictive approaches to patient stratification, and mathematical models of intra- and inter-cellular processes.
Prior biological or clinical expertise is not required – experience of applying machine learning to real-world problems and a strong interest in the interdisciplinary application of predictive methods to life sciences data are imperative.
Responsibilities include, but are not limited to: Requirements: The position presents a unique opportunity to experience research in an industry setting and to contribute to helping patients with unmet medical need, while maintaining a link to academic research (publication is encouraged).
Machine Learning Research Scientist
Over the past three years, we have been able to connect with over 150,000 retail point of sales location in 10 countries and create a database of over $100 billion in first party retail transactional data.
As a Research Scientist, you will own all aspects of the research process such as literature review, data collection, data processing and cleansing, feature engineering, modelling, writing papers and presenting at academic conferences.
- On Thursday, January 17, 2019
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