Our Expertise

Our experts couple their knowledge in data science with backgrounds in consulting, financial services, and business. This enables RRDS to excel at delivering practical, rigorous, and polished solutions to real-world business conundrums.

Since our founding, the team has grown to include PhD-level data scientists, statisticians, developers and MBAs with the cross-industry and academic expertise to help clients solve their hardest data science problems.


Read Our Case Studies

Network Optimization

Need to optimize logistics or match inventory? RRDS has experience solving these tough problems using specialized algorithms like Dijkstra and Yen’s. Our team focuses on network design and optimal control using both applied-theory and data-driven approaches.

One example was when we worked with a shipping company to build a dual network strategy that had to balance a fast but costly solution with a slow and cheaper one. The complexity tested the limits of available computational power, but we were able to find an approximation that was both accurate and scalable.


Predictive Analytics and Maintenance

Looking to decrease costs and increase efficiency with specialized predictive analytics? Working side-by-side with subject matter experts, we can quickly identify whether a particular component or process would be a good candidate for unsupervised or semi-supervised learning.

In one case, we built a new method based on changepoint detection to help a leading industrials company identify potentially troublesome units earlier in their lifecycle, thus reducing costs and return maintenance visits.


Web Scraping

Are you making use of the richest pool of data in history? We have the tools and capability to build fully and partially-automated solutions to harvest primary data directly from the internet.

After the Sandvig v. Sessions ruling that web scraping is allowable regardless of TOS language, we are now able to enrich your existing data with new sources of information. Clients have used web-scraped data to investigate correlations between their internal KPIs and weather, macroeconomic factors, competitor behavior, and customer preferences.

We have experience scraping multiple sources and cleaning and aggregating the results into analyzable form. One of our toughest scraping problems required a semi-automated approach that paired our software systems with human judgement to map out a particularly fragmented and rapidly evolving industry.


Solutions at Scale

Want analytics that will work even at scale? We work hard to ensure the solutions we provide are well-tested and robust. We have R and Python developers on staff who follow software engineering best practices including regular refactoring, active versioning, and rigorous unit testing.

We typically use open source solutions because we find those environments more dynamic and adaptable. However, we have experience with the top commercial packages as well, depending on client preference. Our work has been used in Fortune 500 companies like GE, Kraft, and Ingersoll Rand.


Database Expertise

Already have database infrastructure in place? Working with your internal IT and data engineering teams, we can make a plan of action for how best to work within your existing infrastructure or make improvements to facilitate scale and speed. We’re equally comfortable with NoSQL and relational databases.


Visualization

Need to convey results in concise and actionable manner? We can develop visualization and reporting tools that will make it easy to interpret and utilize the analytics that we’ve built. We have created dashboards in Tableau and made bespoke web-based visualizations using Javascript frameworks like D3, Chartjs, and React. For those most comfortable in Powerpoint, we can also develop a polished template and programmatically pre-formatted outputs.


Translating Business Problems into Data Science Solutions

Unsure if data science is the answer? We can help you analyze your problem and quickly determine the best approach to solve it. We have data scientists who come from the investment world and who specialize in bringing technical products to market. Our work has led directly to patent pending solutions and in some cases, has had direct bottom line impact for clients.

We have worked with firms who are new to data science and are looking to build a systematic approach to rolling out analytics. We have also worked with early stage ventures and portfolio companies to assess their internal data and brainstorm avenues for monetizing and productizing it.


A New Strategy Framework

Not a data scientist but curious about how machine learning and data science could help you? In early 2018, we developed a framework to help non-technical business and line managers successfully navigate data science initiatives. Our framework expands the typical strategic planning concepts beyond strategy and tactics to include a stakeholder assessment and a mapping of operational capabilities.

In our experience, taking time to consider the larger environment in which advanced analytics will operate can mean the difference between solutions that wither on the vine and those that ultimately get deployed. As a team, we know what it takes to successfully translate business questions and use cases into a working data science approach.