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Proven understanding of economics, finance, and investing and aptitude with relevant tools including programming, econometrics, and other market and economic data programs. Reporting to the Managing Director of Research, the research analyst will work closely with analysts on the Asset Allocation Research Team and other colleagues to support day-to-day research needs.
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Knowledge of the application of statistics to economics, including econometrics or regression analysis. Experience with a statistical computing environment such as Python, Stata, R, or MATLAB.
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BS/MS/PhD in Econometrics, Actuarial Science, Data Science, Health Outcomes, Epidemiology, Statistics, or in any technical field that provides a solid basis for analytics highly desired. Experience in Healthcare analytics (preferably PBM Analytics), Clinical Outcomes, Real World Evidence, Care Management Programs.
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Qualifications Expertise in statistics, econometrics, and quantitative analysis, with a solid understanding of financial markets, investment instruments, and portfolio theory. Master's or Ph. D. (or equivalent experience) in a quantitative field such as Mathematics, Statistics, Econometrics, Financial Engineering, or a related discipline.
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Excellent quantitative skills from training in econometrics or statistics, and extensive experience in utilizing those skills in empirical research. The firm has capabilities in systematic responsible investing, offering dedicated quantitative strategies and incorporating proprietary ESG and Climate alpha signals across a diverse range of strategies.
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Cornerstone Research offers candidates pursuing doctoral studies in finance, economics, econometrics, accounting, or marketing the opportunity to join the firm for six to twelve weeks to gain first-hand experience in our work in the role of a Summer Associate.
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Degree in statistics, econometrics, applied math, or a quantitative behavioral sciences field is required. Demonstrable knowledge of, and practical experience applying, data mining methodologies, natural language processing, and machine learning algorithms (e.g. regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision tree methods.
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Cambridge Econometrics es una consultora económica independiente líder y figura en la lista del Financial Times como una de las principales consultorías de gestión. Cambridge Econometrics es una consultora económica independiente líder y figura en la lista del Financial Times como una de las principales consultorías de gestión.
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Our ideal candidate will bring a solid quantitative skillset at the cross-section of data science, statistics, and econometrics combined with the ability to effectively navigate a consulting firm’s dynamic and collaborative environment.
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Requires a Masters degree in a quantitative biomedical science field such as bioinformatics; biostatistics; quantitative epidemiology; statistical genetics; econometrics or systems biology; data science; and 0-3 years experience as a professional quantitative scientist.
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Doctoral degree (PhD or PharmD, or MD) preferred in related field and experience conducting HEVA research (Related fields include Public Health-Health Policy & Management/Health Services Research/Epidemiology/Outcomes Research/Health Economics, Economics/Econometrics, Psychometrics, Statistics/Biostatistics, Pharmacoeconomics/Pharmacy Administration.
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M.S. (or higher degree) in a quantitative field such as Data Science, Statistics, Biostatistics, Econometrics, Economics, or engineering or relevant comparable background. Familiarity with HPC, Databricks, and other similar platforms.
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Successful candidates in this role will have experience in travel demand modeling, skills in econometrics and programming, an aptitude for process development and maintenance, and a preference to work in a team environment that promotes growth opportunities to all members.
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The position will expose candidates to applied quantitative and qualitative research and to executives, analysts, and investors in the field.
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Understanding of statistical applications in economics (including econometrics or regression analysis). Experience with statistical computing environments such as Python, Stata, R, or MATLAB. Familiarity with probability, statistics, linear regression, time-series analysis, linear algebra, calculus, optimization, and portfolio theory.
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econometrics job in Boston, MA
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