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Statistics, probability based calculations, and stochastic calculus; Data analysis, times series analysis and machine learning skills; Fixed income market data and fixed income financial product knowledge; Investment and quantitative methods; Risk management, portfolio optimization and strategy research.
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Demonstrate considerable knowledge and analytic capabilities through the development of quantitative data analysis and data mining solutions, emphasizing the development of database driven reports and analyses.
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Familiarity of R, SQL and data visualization tools a plus (ie Looker, Tableau) Reporting to the Associate Director, Insights & External Research , this new role requires a blend of hands-on data & insight mining and critical thinking.
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Design, code, test and implement quantitative models, leveraging data science techniques, in machine/deep learning and NLP. Master's degree in mathematics, Financial Engineering, Data Science, or related program with experience in mathematical modeling and quantitative methods.
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2+ years of hands-on experience with data science and analytics, modeling platforms, data engineering software and visualization tools (e.g. Advanced SQL, PL/SQL, R, Python, SAP HANA, Spotfire, Tableau, Hadoop, Redshift.
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Understanding of quantitative techniques and methods, statistics and econometrics - including probability, linear regression and time series data analysis and optimizations. Full stack software engineering experience, with proven experience in data visualization modules or frameworks like Python Dash and R Shiny.
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We are looking for a Senior Quantitative Developer that will be a part of a dynamic and fast-paced development team within Quantitative Research and Investment Technology supporting Fidelity Asset Management Solutions (FAMS) researchers and analysts.
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We are looking for a Senior Quantitative Scientist with data science, machine learning, and natural language processing (NLP) expertise that will work closely with clinical structured and unstructured text data derived from electronic health records in support of Verana Qdata® development which enables insight generation.
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3+ years of hands-on experience as a quantitative developer developing financial models and software solutions. Experience working with financial data sets like Factset and Bloomberg a plus.
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Advanced degree (or equivalent) in Financial Engineering / Quantitative Finance, Math, Statistics, Data Science, Engineering, Economics, or other relevant program. Full-time relevant work experience in credit analysis of debt / capital markets, credit analysis / research, quantitative finance, model development or validation.
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Degree must be earned in a related field such as statistics, data science, applied mathematics, computer science, information systems, or other quantitative and computational discipline.
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Experience programming using quantitative, procedural, and statistical programming languages such as R, Python, SQL, Spark, and Matlab. Experience programming and reviewing code using statistical and data software tools like R, Python, SQL, Spark, Scala, etc.
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Proficiently uses statistical programming languages and tools appropriate for data science domains. Experience successfully using Big Data technologies like Hadoop, Spark, Hive, NoSQL, in-memory data stores, etc., and Cloud technologies such as AWS, Azure, etc.
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Use industry leading data science and artificial intelligence (AI) practices to deliver on Intermountain Health's mission to 'Help people live the healthiest lives possible'; making healthcare more affordable and higher quality; and making a difference in the patients and communities we serve.
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Data Scientists develop end-to-end data science applications that apply predictive, prescriptive, and cognitive analytic methods to system-wide clinical and operational strategic initiatives.
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