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Hands-on experience in application of advanced analytics and statistical methods on large and disparate datasets preferably in the context of omnichannel marketing, specifically in statistical analysis, modelling, machine Learning, and artificial intelligence.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency.
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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. Specialized experience for this position includes: Experience applying analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory; link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the study.
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Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling.
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The LGR is in search of a motivated computational biologist/bioinformatician, who will use their skills as a seasoned, experienced bioinformatics programming professional with a broad understanding of computational algorithms and systems to apply computational and statistical methods to analyze and interpret data obtained from the next generation of functional genomics screens.
ExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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Thorough knowledge of bioinformatics and machine learning methods used in image processing for high-throughput screens. Fluency in data science methods, including clustering, dimensional reduction and basic machine learning concepts.
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Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch.
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Experience with machine learning and AI in python with Tensorflow/Pytorch. Mathematical background in statistical signal processing, estimation, and detection. Simulate hardware and wireless channel impairments of L1/PHY digital modulations (FSK, PSK, OFDM) to understand system performance, such as I/Q imbalance, clock synchronization, ADC noise, and AGC loop optimization.
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Job Summary:The Software Engineering Senior Associate, Valuation & Capital Market Analysis – Complex Financial Instruments will be a member of the Data Science team that builds Python based models and related infrastructure to speed up the development and deployment of machine language (ML), statistical and mathematical models at scale and bring game-changing impact to our client’s decisioning.
$90,000 - $115,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are seeking a Lead Machine Learning Scientist who possesses in-depth knowledge of machine learning and statistical signal processing along with strong programming and prototyping skills to join the Technology Development Team. This team sits at the intersection of hardware, data and user interface and evaluates early stage technologies to translate them into experiences that improve our users' lives.
$200,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Showcase solid theoretical knowledge of Machine Learning and Statistical concepts, including Deep Learning, as well as performance tradeoffs. (1) Python Programming; (2) AWS; (3) Docker; (4) Pandas; (5) Tensorflow or Pytorch; (6) SQL; (7) machine learning model development; and (8) extracting insights from offline and online customer data.
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Ideal candidates are highly collaborative problem-solvers specializing in data science, statistical, and/or machine learning methods and tools, and have worked with various forms of data, including text.
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Use statistical modeling techniques to develop northstar metrics and KPIs to help provide a more rigorous data-driven approach to manage the Uber infrastructure. B.S. degree in Computer Science, Statistics, Economics, Mathematics, Machine Learning, Operations Research, or other quantitative fields, or equivalent industry experience.
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Drive research and development of statistical, machine learning models, network clustering algorithm to develop narrative analytics tools with in-house and outsourced data science and/or machine learning teams.
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5+ year expertise in full-stack or machine learning or artificial Intelligence engineering. Knowledge of data analysis, data visualization, and statistical techniques. Knowledge of industry trends and advancements in AI and machine learning.
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machine statistical jobs in San Francisco, CA
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