Data Science & Statistical Modeling

One of the most pressing challenges companies face today is how to harness the ever-growing expanse of available data to help solve real-world problems. Analysis Group clients benefit from the depth of our quantitative expertise in handling big data, our grasp of how data can help inform critical decision-making processes, and our understanding of the technological landscape. Our data science experts apply a number of statistical approaches and methods, including machine learning, natural language processing (NLP), and data visualization.

We go beyond traditional analytics and focus on extracting knowledge and insights from the data, identifying patterns and generating more accurate and powerful predictive models that help inform client decisions. Regardless of the approach taken, we aim to present our analyses in compelling ways that are easy to understand.

These statistical techniques can be applied in litigation related to antitrust and competition; intellectual property; general causation assessment; and securities, financial products, and institutions; among other areas. They can also support clients in non-litigation contexts, for example in health care analyses, and with market research and survey design and implementation

The potential applications of data science to economics, finance, health care analytics, and business strategy are numerous and wide-ranging. They include:

  • Analyzing online product reviews to help determine whether and to what extent allegedly infringed features made a difference in consumers' purchasing decisions
  • Using NLP to detect fraud, including by analyzing the keyword frequency and phrase structure of insurance claims
  • Using machine learning to detect securities market manipulation
  • Predicting the prevalence of an undiagnosed or under-diagnosed disease that otherwise would have been elusive¬†
  • Using big data algorithms to identify adverse events in social media
  • Using predictive analytics to help forecast the market demand for new products or features and/or the success of marketing campaigns¬†