"The unity of all science consists alone in its method, not in its material."
- Karl Pearson, The Grammar of Science (1892)
Methods Consultants was formed in 2009 - before words like Big Data and Artificial Intelligence were even a twinkle in the eye of Harvard Business Review - with the goal of helping clients make sense of quantitative data.
Over the last decade, we have helped clients from nearly every industry leverage data to improve decision-making. We are not industry-specific, we are data-specific. Nonetheless, we have particular strengths in the following areas:
We have long-standing relationships with multiple large medical systems to analyze patient outcomes data, reducing hospital costs and patient complications.
We have repeatedly been called on to serve as consultants and expert witnesses in complex litigation.
We have developed client-specific applications to automate the forecasting of equity moves on the basis of key signals our clients rely on.
Clients have relied on us to perform advanced statistical modeling for post-market surveillance, advertising ROI, and optimizing the geographical location for new establishments.
We have developed statistical analysis plans for companies submitting their products and devices to the FDA for approval, and our analysis has helped demonstrate that the products conform to the manufacturer's claims.
Our data scientists have assisted researchers from nearly every discipline that believes in objective truth (no, not all of them do...) get published in peer-reviewed journals and acquire highly competitive grants. Every year we appear as co-authors on published manuscripts for our work performing the quantitative analysis.
What Makes Us Different?
- Experience in all areas of data science. Don't hire a statistician to build a dashboard for forecasting, and don't ask a dashboard builder to perform forecasting. We make sure you get the specific expertise.
- Large cost savings. While there are off-the-shelf data analysis and visualization software options that are very powerful, they all suffer from the same two shortcomings: high licensing costs and limited extensibility. We work extensively with both R and Python, two open-source alternatives that can handle the entire data science pipeline and do not require tens of thousands of dollars in annual licensing fees.
- Transparent, replicable analysis. Every line of analysis and software code is saved, annotated, and strictly version-controlled using private git repositories. This allows you and us to replicate any analysis no matter how much time passes.
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