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Demonstrated experience in data mining, data visualization, statistical analysis, and machine learning. Demonstrated experience in data mining, data visualization, statistical analysis, and machine learning.
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Lead the direction and development of cutting edge research in statistical modeling and inference of biological problems (including cancer research, genomics, computational biology/bioinformatics, immunology, therapeutics, and more.
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Extensive experience solving analytical problems using quantitative approaches including in the fields of Machine Learning, Statistical Modelling, Forecasting, Econometrics or other related fields.
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As a part of the fundamentals & structuring team, the quant modeler will be responsible for a variety of activities from short and long-term econometric or statistical analysis of power markets and adding quantitative power to fundamental market analysis to assisting structuring and BESS modeling activities and supporting trading/optimization/hedging.
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Solid theoretical knowledge of Machine Learning and Statistical concepts, including Deep Learning, as well as performance tradeoffs. 2+ years of hands-on, post-grad, non-internship professional experience with Machine Learning in a production-based environment.
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Develop and deploy advanced analytical methods to improve our fraud detection and prevention capabilities (e.g., statistical inference, machine learning or graph analysis) A background in machine learning (i.e., constructing ML models, feature engineering, hyperparameter tuning) is a plus.
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6 years of industry data science experience, ideally in the health space working with commercial data Extensive experience in data mining, machine learning, statistical analysis techniques and ML algorithms for classification, regression, clustering, anomaly detection.
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Deploy and optimize machine learning solutions on massive datasets using big data technologies. Knowledge of statistical techniques, linear algebra, numerical optimization. Leverage recent advances in machine learning technologies and oversee the team's training.
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Hands-on experience with statistical tools (e.g. SAS, R, Python) Machine Learning and Deep Learning experience. In addition to designing and conducting product experiments, this data scientist will leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources, analyze product usage patterns, and make actionable recommendations using statistical modeling, business understanding and common sense.
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Understanding of data science/machine learning models and algorithms, not limited to: deep learning (CNN, RNN etc), decision trees (e.g. xgboost, random forest), unsupervised techniques (e.g. clustering, anomaly detection), natural language processing and statistical methods.
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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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Knowledge of the mathematical and statistical fields that underpin data science. Applies machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within.
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You’ll conduct quantitative research to inform product strategy and opportunities, design metrics to help track goals and make decisions, devise learning methods (including experiments) to test hypotheses, and work closely with our machine learning and data engineering teams on building MVP user-facing data products.
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Statistical knowledge and extreme proficiency in SQL. Comfortable with R, Python and Tableau. You will be impacting every aspect of the business and it will require various techniques, from diving deep into data with SQL and Big Data tools, all the way to deploying modern machine learning models.
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Proficiency in statistical programming languages and tools such as Python and R. Knowledge of machine learning techniques and their application in predictive modeling and analysis of healthcare data.
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machine statistical jobs in San Francisco, CA
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