Data science has become increasingly important in investing and finance. With massive amounts of data being generated, data science techniques like machine learning allow investors to gain valuable insights from data. This article summarizes key information from pdf attachments on how data science is transforming investing.
Data science helps generate alpha and automate processes
The JPMorgan pdf highlights how machine learning can help investors generate alpha by analyzing alternative datasets and predicting key financial indicators. It can also automate manual processes like fraud detection. Overall, data science is becoming crucial for portfolio managers, analysts and executives in finance.
Skills needed include programming, data wrangling and domain expertise
The pdf from eFinancialCareers emphasizes that data scientists in finance need both tech skills like Python programming and expertise in markets and economics. Raw data analysis skills aren’t enough – you need to interpret the data and results in a business context. Top firms are looking for data scientists with all these skills.
Popular Coursera courses teach data science tools and techniques
The Quora thread lists many Coursera courses that teach practical data science skills, including Python, SQL, data visualization, machine learning and deep learning. These equip students with hands-on abilities to gather, process, analyze and interpret data using common data science tools.
Data science is transforming investing by extracting insights from new data sources. Domain knowledge and programming skills are both crucial. Taking Coursera courses can help develop data science abilities.