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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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The role will require the ability to flex between technical engineering of the platform and hands on working knowledge creating data science applications as a user of the platform.
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You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. Business Card & Payments Data Science team builds industry leading machine learning models to empower credit underwriting decisionings, supports advancement in Capital One business card product strategies, decisioning and credit infrastructures.
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6) Fluent in using R, Python or equivalent statistical analysis software such as SAS, Matlab (7) Hands-on Experience with Apache Spark, NoSQL techniques and data acquisition tools. (4) 13+ years applied experience devising, deploying and servicing statistical and machine learning models on massive datasets; extensive experience in wrangling data from its raw forms to a state suitable for application of advanced algorithms.
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As a Data Scientist Lead - VP, you will be hands-on in analyzing large-scale data to create analytical, statistical, and data science models to uncover underlying patterns and drivers to business questions in employee relations, conduct, security, compliance, customer complaints, etc.
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The complexity and scale of data being generated has grown significantly and requires strong scientific contributions to integrate different approaches in modeling, statistics, and data science to bring value to the Eisai portfolio.
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S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on ML scientists and NLP/Gen AI/ LLM scientists to grow into the next step in their career journey and apply her or his technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas.
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We are seeking highly motivated postdoctoral researchers in biomedical informatics and data science to work on projects focused on the development of biomedical blockchain, clinical predictive models, and blockchain-based privacy-preserving learning.
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Expertise in machine learning, AI, and advanced analytics, with hands-on experience in Python, R, SQL, or other data analysis programming languages. OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND.
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As the VP of Data Science, you will lead and mentor a team of data scientists and machine learning engineers to deliver innovative and scalable solutions that meet the needs of our customers.
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Expert user of Big Data technologies/platforms, statistical platforms and data visualization tools, advanced SQL skills, hands-on experience with machine learning, predictive modeling and statistical analysis techniques.
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Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence technologies, and evaluate their potential impact on our business and industry.
$315,000 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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Apply hands-on data science techniques, including advanced analytics, machine learning, statistics, etc. Solid theoretical background in data analytics, data mining, machine learning, and statistics.
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More than 10 years of hands-on Experience with Big Data frameworksPractical experience with Machine Learning and Deep Learning, GenAI techniquesExperience developing data products, technologies and platformsExperience with Public Cloud technologies such as AWS or Google CloudExcellent communication skills: Ability to translate technical and analytical metrics into simple content and present to business partners as well as senior leadership.
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