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Use PowerBI, Tableau, Excel, Snowflake, statistical computer languages (R, Python, SQL, etc.) Advanced skills in statistical computer languages (R, Python, SQL, etc.) We own and operate leading entertainment and news brands, including NBC, NBC News, MSNBC, CNBC, NBC Sports, Telemundo, NBC Local Stations, Bravo, USA Network, and Peacock, our premium ad-supported streaming service.
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Fluency in the languages of data manipulation (e.g., SQL) and statistical analysis (e.g., R or Python/NumPy), with ability to code (e.g., PHP) a plus, Java, Ruby, Clojure, Matlab, Pig or SQL. Sitting at the intersection of quantitative and investment analysis, the professional will be a "hands-on" player/coach building a team of Data Scientists focused on the implementation of Data Science technologies, techniques and methodologies leveraging Artificial Intelligence (AI) and Machine Learning, advanced analytics, and statistical methods.
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Apply analytical and statistical programming as well as visualization tools to drive the end-to-end analytical process. Requirements: Bachelor's degree in Engineering, Technology, Computer Science, or closely related field, plus one year of professional experience building, stabilizing, validating, and monitoring statistical models to ensure that they meet the retail sector client guidelines.
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We are seeking a highly skilled and motivated Principal Statistical Programmer with expertise in pharmacokinetics (PK) and pharmacodynamics (PD) to join our dynamic FSP team. Qualifications:Substantial experience in statistical programming using SAS, R, or other relevant programming languages within the pharmaceutical or biotech industry.
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Experience with programming languages / statistical software (e.g., EViews, Python, R, Excel VBA) is a plus and advanced Excel and Microsoft Office skills are required. Experience in forecasting, statistical analysis or research on macroeconomic and / or financial variables would be considered a plus.
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Analyzing, evaluating, and interpreting vegetation data using spatial GIS software (e.g., ESRI ArcGIS) and statistical programs (e.g., RStudio); A diploma, undergraduate or graduate degree in Environmental Science, Biology, Ecology, Ecological Restoration or another relevant natural resource management-related field.
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With a focus on innovation, we employ state-of-the-art statistical and AI methodologies to reveal disease mechanisms and pioneer precision medicine tools. Statistical modeling of longitudinal data and the implementation of machine learning algorithms will be central to your role.
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Extensive experience with statistical analysis, data modeling, and data visualization tools such as R, Python, SQL, and Tableau. The ideal candidate will have a deep understanding of Direct-to-Consumer research methodologies, data analysis, and statistical modeling, as well as a strong business acumen.
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Has advanced understanding, and can apply knowledge of, complex mathematical techniques (but not limited to): statistical outlier methods, logistic regression, natural language processing (NLP), and various machine learning methods (e.g., random forest, XGBoost, etc.
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Experience with statistical analysis tools such as Excel, SQL, Python, R, Stata, and data visualization tools such as Microstrategy or Power BI. Experience with statistical analysis tools such as Excel, SQL, Python, R, Stata, and data visualization tools such as Microstrategy or Power BI.
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Must have 3 years of recent experience in financial engineering or statistical software package such as a Matlab, Stata, Bloomberg, or MS Excel/VBA. Analyze and develop models to value a variety of financial instruments, using option pricing theory, fixed income and structured finance models, Monte Carlo simulation, statistical analysis, and other techniques from the financial engineering literature.
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Strong understanding of the use of computer technology in financial and economic research, with statistical programming skills (Python, Java), data management and retrieval acumen (preferably SQL/Spark) and Linux literacy.
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Strong quantitative/statistical skills in the field of predictive analytics with broad knowledge of regression analysis, time series analysis, Monte Carlo simulations, artificial intelligence, and data mining algorithms.
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The Fair Lending Analytics Director manages the development and implementation of modeling and statistical technologies to ensure the Bank's policies, products, practices, and models are fair. Review, interpret, and communicate the results of fair lending statistical analysis to a wide range of audiences, including auditors, regulators, Board of Directors, Executive Suite, oversight committees, Senior Management, and Bank personnel.
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The GRR Report Owner of Country Exposure, Legal Entity, and Systemic Risk will be the key point of contact as it relates to providing relevant financial information and statistical data to regulators, responding to inquiries, and having recurring meetings, as requested, involving the Federal Reserve Bank (FRB), the Office of the Comptroller of the Currency (OCC) and the Federal Deposit Insurance Corp (FDIC.
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psychometrics statistical jobs in New York, NY
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