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Experience with deep learning libraries (e.g. PyTorch, Jax, Tensorflow) and platforms, multi-GPU training, and statistical analyses of observational and experimental data. Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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We are searching for a (Senior) ML/AI Data Scientist with strong experience in deep learning and AI to develop and productionize innovative models that enhance and accelerate our drug discovery and clinical translation efforts.
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Must have: Two (2) years of experience with the following: basic programming knowledge; deep learning tools such as Keras, Tensorflow, Pytorch, or Torch; big data tools such as Pyspark, Hadoop, ElasticSearch, or Apache; analytics tools such as Pandas, NumPy, Dask, or Polars; and Kubernetes, Kafka, Docker, or Cassandra.
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Experience in Natural Language Processing (NLP) and Deep Learning. This individual will collaborate with other data scientists and quants to prototype, learn, and ultimately deliver investments solutions using techniques such as machine learning, artificial intelligence, and graph learning.
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Deep Learning Research : Stay at the forefront of deep learning research and methodologies, applying innovative techniques to address challenges in NLP tasks, such as named entity recognition, sentiment analysis, language translation, and more.
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Hands-on experience with machine learning, deep learning, statistical modeling, causal inference, multivariate regression, and classification. Experience delivering on Data Science projects using predictive technologies, forecasting, natural language processing, artificial intelligence, or machine learning.
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Some of this experience needs to be with NLP and deep learning technologies. Quantization and Model Optimization : Implement advanced quantization techniques to optimize deep learning models for efficient deployment on resource-constrained environments, ensuring minimal loss in performance while reducing memory and computational demands.
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Strong experience writing code in Python, and with appropriate deep learning packages such as PyTorch, TensorFlow. Success in the role will require hands-on experience developing and refining deep learning models in a relevant domain or data type, a pragmatic ‘test and learn’ mindset, and the ability to collaborate effectively with biologists and chemists to tailor analysis to specific scientific contexts.
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Collaborate with colleagues from diverse scientific background to identify problems and opportunities; combine techniques from computational chemistry, computational biology, and AI/ML, particularly utilizing recent deep learning techniques, to rapidly develop powerful computational solutions.
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Deep expertise in statistical and machine learning methods for go-to-market attribution and hands-on experience with building end-to-end attribution systems that may include Marketing Mix Modeling (MMM) algorithmic multi-touch attribution (MTA.
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The ideal candidate will be proficient in advanced machine learning and deep learning techniques, with a strong background in image analysis, high-performance computing, and a keen interest in the intersection of computational science and biology.
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Recognized industry expertise in 2-3 of the following: Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning and Statistical modeling. As a Sr. Director & Data Scientist, you will lead a team responsible for challenging conventional thinking and use data to communicate insights and tell the story to business and analytics leadership.
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Advanced degree in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields. 5+ years of prior work experience as a Data Scientist.
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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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Experience with deep learning frameworks, such as Pytorch, TensorFlow, HuggingFace. ; (2) Establish robust and scalable data management pipeline; (3) Apply Artificial Intelligence in different business domains (Data Science, Machine Learning, Statistical Analysis, etc.
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deep learning scientist jobs in Boston, MA
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