MBS Externship Exchange

image box

The Rutgers Master of Business and Science (MBS) degree program runs an Externship Exchange opportunity for students and companies where we match up MBS students to corporate sponsored small projects. All projects and teams are directed by the Externship Coordinator, Dr. Nelson.

For companies:  We have companies submit projects related to any of our science concentrations. For example, we can conduct a research study, analyze big data, perform user experience design for customer improvement, create sustainability ideas, design new packaging, or any project that can add value to your team and to our MBS students. (See below for other examples.) Companies interested in submitting a project, please contact the Externship Exchange Coordinator, Dr. Christie Nelson at cnelson@dimacs.rutgers.edu.  For other ways to connect with our program, please see our Employer Partnerships page.

For students: The MBS Externship Exchange is a great way to get involved. Students can take the Externship Exchange for credit or just participate as "club". Projects typically run between 6-12 weeks, and students usually work 8-10 hours per week on the Externship projects. Often projects are completed by a few teams of students in groups of 2-3. Since students work on real projects, they often sign confidentially agreements with the company or organization. View some sample projects below.

Webinars for summer 2018 externship exchange - please see here 

Fall 2017

Wall Street Boot Camp

Mergers & Acquisition Financial Case Study

  • Participated in a boot camp to understand how corporate credit rating works, focused specifically on mergers and acquisitions.
  • Mentor: Ben Nelson, Vice President & Senior Credit Officer at Moody’s Investors Service
  • Students: Subhadra Akella, Advait Deodikar, Mengxi Liu, Vincent Omolo and Kevin Rupert

Robert Wood Johnson Medical School

Analysis of MIMIC Medical ER Data

  • Students first completed CITI training for handling sensitive data and then worked with a medical doctor to analyze hospital ERs and ICU department admissions. This was performed on data from the MIMIC medical database.
  • Mentors: Dr. Saqib Baig, Pulmonary & Critical Care Fellow; Dr. Christie Nelson, Assistant Research Professor; and Dr. Karen Bemis, Research Associate
  • Students: Siddhant Garg and Denis Ngyuen

NJ State Police Office of Forensic Sciences

Ballistics Data Analysis

  • Data science project exploring several ballistic forensic research questions, utilizing data from GUN-OPS and NIBIN.
  • Students: Aishwarya Gunde, Usama N. Saifi, and Ingrid Wijaya

Nielsen

Human Rights and The Supply Chain

  • 7 in 10 corporate procurement professionals believe forced labor may be in their supply chains. The UK Modern Slavery Act and the Dodd Frank Conflict Minerals disclosure have been regulatory responses to this problem. Students examined this topic, and focused on corporate disclosures on forced labor and conflict minerals in the electronic industry as relating to human rights and the supply chain. A comparative analysis of public disclosures related to the UK Modern Slavery Act and public disclosures related to conflict materials was performed.
  • Mentor: Jocelyn Azada
  • Student: Jay Patel

Impact Sourcing

  • Impact sourcing is an innovative sourcing practice with a mission to eradicate poverty through procurement. This research provided support in the development of resources that would be useful to Nielsen as well as other large companies who are implementing impact sourcing as part of the Global Impact Sourcing Coalition. An analysis of impact sourcing for large corporations was performed, emphasizing success case studies for impact sourcing. The student also created a directory of major impact sourcing companies.
  • Mentor: Jocelyn Azada
  • Student: Subhadra Akella

Social Label Consumer Data Point

  • In recognition of the rise of conscious consumers in the U.S., the goal of this project for Nielsen was to evaluate current data points on forced labor and human trafficking in global supply chains and recommend a consumer-friendly easy-to-use “data point” that could quickly and meaningfully communicate to consumers what the risk of forced labor/human trafficking is for a particular consumer-packaged goods product.
  • Mentor: Jocelyn Azada
  • Student: Yue Liu

 

Center for Discrete Mathematics and Theoretical Computer Science (DIMACS)

High Dimensional Data Project

  • Developed a code and computed the intrinsic dimension of various real datasets (LIDAR data, simulated random data, etc.), comparing different algorithms. Research leveraged work from “Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis” by F. Patricia Medina, Linda Ness, Melanie Weber, and Karamatou Yacoubou Djima.
  • Mentor: Dr. Linda Ness, Research Scientist
  • Students: Michael Albuquerque, Kafung Mok, Ranvir Singh, and Narendran Sundara Mahalingam

CCICADA, a Dept. of Homeland Security Center of Excellence

Drone Detection Experiments at a Large Stadium Venue

  • Created and implemented an experimental design to understand drone detection software, and then analyzed performance.
  • Mentor: Dr. Christie Nelson, Assistant Research Professor
  • Students: Yue Liu and Ivan Mera

Social science project involving reviewing literature on the behaviors of violent extremists and then creating recommendations for a government hotline

  • Social science project which involved a literature review into behaviors of violent extremists and then creating recommendations for a government hotline number.
  • Mentor: Dr. Christie Nelson, Assistant Research Professor
  • Student: Ivan Mera

Analysis of a Large Sports Team’s Social Media

  • Performed statistical analysis and machine learning modeling on Twitter and Instagram social media data of a major sports team to understand implications for stadium security.
  • Mentor: Christie Nelson, Assistant Research Professor
  • Students: Ketan Walia and Ivan Mera
Summer 2017

Wall Street Boot Camp

Paint & Coatings Financial Case Study

  • Participated in a summer long boot camp to understand how corporate credit rating worked and learned to model like a Wall Street analyst. Led by a Wall Street professional. Student groups modeled five of the major paint and coatings companies, identifying relevant financial indicators and key drivers of future financial performance. Students learned to break down global business models, forecast financial performance, identify and analyze key financial metrics, apply real-world analytical methodologies, and compare conclusions to market trading prices for stocks and bonds.
  • Mentor: Ben Nelson, Vice President & Senior Credit Officer at Moody’s Investors Service
  • Students: Advait Deodikar, Ankita Gupta, Isha Majmudar, Ivan Mera, Vincent Omolo, Daniel Pittaro, Stephen Taras and Jingwei Zhang

Robert Wood Johnson Medical School

Data Visualization & Logistic Regression Modeling of MIMIC ER Data

  • Students first completed CITI training for handling sensitive data, next performed a background literature review to learn about the topic of medical ICU waiting rooms, and finally worked with a medical doctor to come up with a project goal that may be useful to hospital ERs and ICU departments while utilizing data available in the MIMIC database. Students extracted patients’ medical ICU data from a large SQL database. Once the students had the data in a usable form (after extracting and cleaning the data), they performed exploratory data analysis on certain data fields of interest, and finally built a logistic regression model to predict if ICU patients were at risk for mortality.
  • Mentors: Dr. Saqib Baig, Pulmonary & Critical Care Fellow; Dr. Christie Nelson, Assistant Research Professor; and Dr. Karen Bemis, Research Associate
  • Students: Supreet Kaur, Sri Harsha Reddy Devireddy, Karthik Keertipati, Kartheek Reddy Mondeddu and Siddhant Garg

Johnson & Johnson

Packaging Project

  • Participated in an MBS educational project sponsored by Johnson & Johnson to enhance the consumer experience of an OTC drug delivery system
    • Attended discussions with J&J R&D on the “insights generation to prototype development” process
    • Conducted consumer discussions to uncover insights to drive increased satisfaction with the product usage experience
    • Utilized online category landscape data and consumer insights to generate ideas to improve the primary packaging design
    • Presented lead package design sketches to J&J R&D team for consideration and further development
  • Students: Subhadra Akella, Maria Calderon, Princia Contin, Ria Khetan, Isha Majmudar, Vaishnavi Nanjundaswamy, Sebastian Pesantez, and Constantine Siozopoulos

Rutgers Student Affairs

Diverse Learning Survey Analysis

  • Analyzed early results from the Diverse Learning Environments Survey to aid Rutgers to understand the campus climate. Preprocessed and analyzed survey data in R and SPSS to understand the question response rate, missing values, and responses. Clustering analysis was also performed.
  • Students: Arshi Goyal, Aswani Katari, Shobha Thomas and Hangyu Zhu

NJ Office of Homeland Security and Preparedness / Rutgers IC CAE

Certificate in Intelligence and National Security

  • Learned the basics of intelligence analysis and national security and explored current topics in intelligence and national security. Participated in scenario based simulation exercises with guidance from experienced facilitators from NJOHSP.
  • Student: Ivan Mera

Center for Discrete Mathematics and Theoretical Computer Science (DIMACS)

Inferring Spatio-Temporal Distributional Summaries of Agent Data

  • Examined the flow of agents through a large building with respect to spatio-temporal probability distributions. Analyzed entry/exit points for these agents. Determined spatio-temporal distribution of agents (using binary trees). Calculated average paths for agents using same building entry and exit combinations.
  • Students: Usama N. Saifi, Ranvir Singh, Narendram Sundara Mahalingam

SAS Certification

Learn to Use SAS

  • Some students were interested in learning SAS, so they came up with various topics to explore in order to prepare for a SAS Certification.
  • Mentor: Dr. Karen Bemis, Research Associate
  • Students: Hammad Khan and Sujith Thokala
Spring 2017

CCICADA, a Dept. of Homeland Security Center of Excellence

Professional Sports Team Data Analysis

  • Analyzed a patron satisfaction survey with respect to stadium security, and compared with the team’s patron ticket scan data to discover insights when visualized. Scraped social media data relating to the team for one season.
  • Students: Winston James, Hammad Khan, Aapta Paresh and Yue Liu