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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
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Our deep learning engine automates the translation of patient records into the billing codes used for healthcare provider reimbursement, a process today that costs hospitals in the US $15B+ annually and tens of billions more in errors and denied claims.
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Effectively leverage statistics, machine learning (with an emphasis on deep learning), reinforcement learning, generative AI, and data mining, to support teams in critical business areas and tackle challenging problems with a direct impact on companies OKRs (Objective and Key Results.
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Experience using statistical analysis and computing, machine learning, deep learning, processing large data sets, data visualization, data wrangling, mathematics, and programming.
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11 West 19th Street (22008), United States of America, New York, New YorkPrincipal Data Scientist - Fraud, Deep Learning. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Deep Learning frameworks such as Keras, Tensorflow or PyTorch. Select statistical or Deep Learning models that are best positioned to achieve business results. As a member of the Cyber Technology and Controls Product team you will be part of a highly motivated team that focuses on analyzing data and creating and delivering Machine Learning solutions that will protect the firm from a variety of cyber-related threats.
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Bonus points for if you have experience working with deep learning models such as Tensorflow, Pytorch etc. You have worked with data modeling, configured AB test experimentation, and have experience working in technologies like SQL, ETL, and technologies similar to Spark, Airflow, SQL, data warehousing, etc.
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New York Institute of Technology's six schools and colleges offer undergraduate, graduate, and professional degree programs in in-demand disciplines including computer science, data science, and cybersecurity; biology, health professions, and medicine; architecture and design; engineering; IT and digital technologies; management; and energy and sustainability.
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Maintain a constant, deep knowledge of legal issues related to emerging technologies (i.e., cloud, artificial intelligence/machine learning, data usage, etc. Working with product managers, engineers and other stakeholders across the enterprise including Data and Machine Learning teams, the successful candidate will manage the risks from product development to deployment.
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Amidst rapid growth and evolving challenges, Amazon Publisher Cloud seeks a Principal Scientist with a deep passion for data, innovation, and the drive to explore new frontiers. - Demonstrated ability to shape product strategy with innovative research in deep learning.
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Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently.
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Expertise in traditional statistical analysis, Bayesian modeling, traditional ML, Deep Learning, RL, and optimization, with deep specialization in at least two areas. We are seeking a Principal Data Scientist to manage and grow a portfolio of AICS revenue, lead strategic client relationships, advise clients and Fractal’s leadership on the latest research and best practices, and consult on Fractal’s strategic direction in AI. This is a senior-level leadership role requiring strong technical and executive skills.
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FEATURED BLOG POSTS
5 Common Interview Mistakes
Everyone's interview process is unique in some form or fashion. Like most, your interview process is crafted so you can get the most information out of your candidates to increase hiring confidence and make the right hiring decisions. However, there are often small problems in interview processes that could ultimately affect the success of hiring decisions.
How to Ask Someone to be a Reference + Email Templates
One part of the job-hunting process that frequently gets overlooked is putting together a list of good references. Most of the time we focus on creating the perfect resume, writing an awesome cover letter, and getting our hands on letters of recommendation. We think about what outfit we’ll wear to the job interview, how we’ll answer those tricky questions, and what our career plan looks like. But, in fact, having multiple references lined up who will speak favorably about you to a potential employer is critical to landing a job. This aspect of job searching really can’t be ignored.
Job Rejection Email Response with Examples
Glassdoor estimates that, on average, there are about 250 applicants for every job vacancy out there. If you’ve ever applied for a job, the odds are that you’ve received the dreaded job rejection email.
Structured vs Unstructured Interviews
The goal of an interview is to evaluate candidates based on their skills, personality, and knowledge. You want to choose the BEST candidate from your candidate pool, so the interview is something you can't mess up. As you begin planning your interview process, one of the major decisions you'll face is whether the interview should be a structured vs unstructured interview. So let's take a dive into the differences and sort out which circumstances warrant which interview process.
How to Describe Your Personality with Examples
Imagine you’re in an elevator with the CEO of your dream company and you get to talking. The conversation is going well and you start to imagine yourself working for their company when the CEO turns around and asks you “tell me a bit about yourself.” Would this catch you off guard or would you be able to give a clear and succinct description of who you are?
4 Ways to Make Your Job Posting More Inclusive
According to a Glassdoor survey,
To ATS or not to ATS
As hiring is becoming more analytical and data-driven, companies have found ways to incorporate technology to help hire and recruit more efficiently. ATS, also known as an applicant tracking system, has become one of the most widely adopted technological recruiting tools to date. In fact, according to data from Capterra: