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Quantitative Researcher

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Salaries for Quantitative Researcher

City
Median
New York
$162,000
San Francisco
$210,000
Seattle
$165,000
See all salaries
City
Median
New York
$162,000
San Francisco
$210,000
Seattle
$165,000
Austin
$128,000
Toronto
$147,000
London
£109,000
Paris
€89,000
Berlin
€83,000
Tel Aviv
₪430,000
Singapore
S$131,000
Beijing
¥546,000
Shanghai
¥194,000
Shenzhen
¥580,000
Bengalaru
₹437,000
Delhi
₹1,420,000
Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.

Path to Quantitative Researcher

Take the first step.
We've curated 24 courses to help you on your path to Quantitative Researcher. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

Reading list

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Provides a rigorous treatment of quantitative models used in portfolio management. It covers topics such as asset allocation, risk optimization, and performance evaluation.
Provides a comprehensive overview of quantitative methods for business students and professionals, including descriptive statistics, inferential statistics, and regression analysis. It valuable resource for those who need to make data-driven decisions in the business world.
Provides a comprehensive overview of quantitative trading. It covers topics such as market microstructure, statistical arbitrage, and machine learning.
Provides a practical guide to quantitative finance for practitioners. It covers topics such as portfolio theory, risk management, and derivative pricing.
Offers a comprehensive overview of marketing analytics techniques, covering data collection, data analysis, and data visualization. It provides step-by-step instructions and real-world examples to help readers understand how to use data to improve their marketing campaigns.
Provides a practical guide to quantitative data analysis using R, a statistical software package that is widely used in the social sciences and data science. It covers a wide range of topics, including data management, data analysis, and interpretation of results.
Provides a comprehensive overview of quantitative methods for economics and finance, including econometrics, time series analysis, and forecasting. It valuable resource for economists and financial professionals who need to analyze data to make informed decisions.
This best-selling textbook provides an accessible introduction to quantitative methods for business students. It covers topics such as data collection, descriptive statistics, inferential statistics, and regression analysis.
Covers a wide range of quantitative methods used in the social sciences. It includes topics such as survey research, observational research, and experimental research.
Provides a comprehensive guide to quantitative funds for investors. It covers topics such as fund selection, portfolio construction, and risk management.
Provides a comprehensive overview of advanced quantitative methods for educational research, including multivariate analysis, structural equation modeling, and hierarchical linear modeling. It valuable resource for researchers who need to analyze complex data sets from educational research studies.
Provides a comprehensive overview of quantitative methods for archaeology, including statistical methods, GIS, and remote sensing. It valuable resource for archaeologists who need to analyze data from archaeological excavations and surveys.
Offers a comprehensive overview of web analytics, covering topics such as traffic analysis, conversion optimization, and social media analytics. It good choice for readers who want to learn more about the specific techniques used to analyze web data.
German-language textbook on quantitative empirical social research. It provides a comprehensive overview of the topic, including research design, data collection, data analysis, and interpretation of results. It valuable resource for students and researchers who need to conduct quantitative research in the social sciences.
Offers a practical guide to using analytics to improve marketing performance. It covers topics such as data collection, data analysis, and data visualization.
Offers a comprehensive overview of digital marketing analytics. It covers topics such as web analytics, social media analytics, and search engine marketing analytics.
Provides a comprehensive overview of statistical methods for the social sciences, including descriptive statistics, inferential statistics, and regression analysis. It valuable resource for students and researchers who need to analyze data from surveys, experiments, and other research designs.
Offers a comprehensive overview of marketing analytics and data management. It covers topics such as data collection, data analysis, and data governance.
Provides a comprehensive overview of marketing analytics techniques using the Python programming language. It covers data collection, data analysis, and data visualization, and it includes many helpful examples.
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