AI News, Engineering at Teradata artificial intelligence

Senior Data Scientist

is looking for people that are interested in solving next-generation big data problems leveraging modern and open source tools and frameworks in combination with tried and true best-in-class technologies.

Service Analytics team’s vision is to become the world’s most effective technology support organization, where customer issues are resolved quickly, and avoidable impact is prevented using automated analytics-driven services.

a close-knit multifunctional team of data scientists, software engineers, data engineers, and subject matter experts delivering end to end solutions from research all the way to production.

a senior data scientist, you will take the lead to research, design, prototype, test and document novel algorithms and predictive analytics for automated, near real-time decision making on customer support issues.

will work closely with data engineers and subject matter experts who will assist you in understanding the data.  You will also work closely with software engineers who will assist you in transforming your prototypes into production code.

record of delivering data science including a basic understanding of database systems, software engineering, systems monitoring, and communication to stakeholdersExtensive knowledge of Python (must include SciPy, NumPy, Pandas)Experience working with SQL databasesAbility to collaborate on an interdisciplinary team. Self-starter with a positive attitude, intellectual curiosity and a passion for analytics and solving real-world problemsDemonstrable skills in creative-problem-solving of complex and advanced technical subject matter   Extra

Teradata is looking for people that are interested in solving next-generation big data problems leveraging modern and open source tools and frameworks in combination with tried and true best-in-class technologies.

The Group Teradata Service Analytics team’s vision is to become the world’s most effective technology support organization, where customer issues are resolved quickly, and avoidable impact is prevented using automated analytics-driven services.

We’re a close-knit multifunctional team of data scientists, software engineers, data engineers, and subject matter experts delivering end to end solutions from research all the way to production.

The Work As a senior data scientist, you will take the lead to research, design, prototype, test and document novel algorithms and predictive analytics for automated, near real-time decision making on customer support issues.

You will work closely with data engineers and subject matter experts who will assist you in understanding the data.  You will also work closely with software engineers who will assist you in transforming your prototypes into production code.

We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status.

5 Myths You Have Been Told About Industrial AI

This is a message for the industrial companies, the ones who build, operate, maintain, and rely on large, complex assets, processes, capital equipment, systems, and machinery.

was applied to a series of predictive maintenance problems in the hopes that by simply ingesting large heaps of machine data, the AI could predict which component part of the equipment would fail next.

In the business use context, the AI would utilize data like the equipment type, location, the components of the equipment and how the equipment has been used in its previous life cycle to determine the relevant information.

However, without great effort, these data points are typicallynot available to the data scientist trying to build the AI, unless the company has established its data foundation, or digital thread.

This brings us to the real problem here: the AI is highly dependent on the very manual process of labeling the data to allow the AI to learn to predict or perceive, or distinguish accurately.

Labeling often involves things like tearing down an electronic device to determine where the failure occurred, examining a machine in a failure analysis lab, and x-raying a high-pressure hose to determine if there were defects that lead to its failure.

AI in today’s world is good for tasks that a child could do, these tasks are often those that could be completed in a 15 second timeframe, like differentiating one object from another, detecting sentiment, or recognizing a pattern within a shape.

eSilicon Expands Technical Advisory Board

eSilicon, a leading provider of FinFET ASICs, market-specific IP platforms and advanced 2.5D packaging solutions, announced today the addition of Ron Bodkin to its technical advisory board (TAB), which is focused on guiding the company's development work associated with artificial intelligence ASICs.

Existing members of the TAB include Dr. Dileep Bhandarkar, independent datacenter technologies and neural network consultant, Dr. Michael Orshansky, professor and John E.

"Dileep brings operational data center design experience, Michael and Mattan bring the research perspective and now Ron brings the data science and big data analytics perspective." To

learn more about eSilicon's 7nm AI ASIC capabilities, visit eSilicon's neuASIC web page or contact your eSilicon sales representative directly or via sales@esilicon.com. About

Our ASIC-proven, differentiating IP includes highly configurable 7nm 56G/112G SerDes plus networking-optimized 16/14/7nm FinFET IP platforms featuring HBM2 PHY, TCAM, specialized memory compilers and I/O libraries.

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