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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. You'll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences, and building close-knit relationships across the company.
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Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
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Candidates should demonstrate expert knowledge in one or more of the following areas: data management, machine learning, deep learning, artificial intelligence, data visualization, programming Python, programming in R, databases, and related topics, either through a record of teaching excellence or through industrial experience.
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Experience leading teams in data analytics and data visualization, including selecting and applying the appropriate analytical techniques for statistical analysis, predictive modeling, simulation, and machine learning.
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Fluency with quantitative research methods, which could include multivariate and multilevel regression analysis, difference-in-differences and fixed effects panel designs, propensity or other weighting/matching techniques, synthetic control designs, machine learning and predictive modeling (e.g., random forests and gradient boosted trees), time-to-event or survival analysis with time-varying covariates, interrupted time series studies, and/or composite index creation.
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Undergraduate teaching experience in core topics in Data Science such as programming, data mining, data visualization, Parallel and Distributed Computing, Machine Learning, Big Data Engineering and, Probability and Statistics will be considered an asset.
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Experience: At least 3-7 years of experience in a data science role Skills: Strong theoretical background in and practical experience with optimization, statistical techniques, and machine learning & artificial intelligence models Strong programming skills in Python (or R or Julia) and SQL Extensive experience with standard machine learning libraries (e.g., in Python; Numpy, Pandas, SciPy, Scikit-Learn, PyTorch, TPOT, etc.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Collaborate with cross-functional teams including data scientists and product managers to align machine learning solutions with business objectives.
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Experience may be gained concurrently and must include one (1) year in each of the following:-Building statistical models and machine learning models using large datasets from multiple resources-Working with Customer, Content, or Product data modeling and extraction-Using database technologies such as SQL or ETL-Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata.
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We’re looking for an experienced, product-minded data scientist to join our Data Science & Machine Learning Team focused on the application of data science, machine learning and AI approaches to understanding banking customer behavior and optimizing engagement marketing through our FinTech product platforms.
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In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
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Databricks Machine Learning Certificate Preferable. Net Developer Azure Cloud Data Engineer Azure Databricks Azure Data Factory Azure logic App PowerBi Report Server Python Nice To Have. NET C# skills SSIS Required Skills : Azure.
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As a Director, Data Scientist supporting Group Insurance you will partner with Machine Learning Engineers, Data Engineers, Data Analysts and other professionals to build models to support Life Data Analysis.
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We are seeking computational postdoctoral researchers with a strong background in machine learning and an interest in developing and applying quantitative methods to problems in translational cancer biology and cancer data science.
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machine learning jobs Title: data in New York, NY
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