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Student Resume Book Class of 2019 STUDENT RESUME BOOK [email protected] CLASS OF 2019 PROFILE 46 48% WOMEN CLASS SIZE PRIOR COMPANIES Feldsted & Scolney 2 Amazon.com, Inc Fincare Small Finance Bank American Airlines Group General Electric Co AVERAGE YEARS American Family Insurance Mu Sigma, Inc PRIOR WORK Bank of New York, Qualtrics LLC EXPERIENCE Melloncorp Quantiphi Inc Brookhurst Insurance Skyline Technologies Services TechLoss Consulting & CEB Inc Restoration, Inc Cecil College ThoughtWorks, Inc Darwin Labs US Army Economists, Inc UCSD Guardian United Health Group, Inc PRIOR DEGREE Welch Consulting, Ltd CONCENTRATIONS ZS Associates Inc & BACKGROUND* MATH & STATISTICS 82.61% ENGINEERING 32.61% ECONOMICS 30.43% COMPUTER SCIENCE & IT 19.57% SOCIAL SCIENCES 13.04% HUMANITIES 10.87% BUSINESS 8.70% OTHER SCIENCES 8.70% *many students had multiple majors or OTHER 8.70% specializations; for example, of the 82.61% of students with a math and/or statistics DATA SCIENCE 2.17% background, most had an additional major or concentration and therefore are represented in additional categories. 0 20 40 60 80 100 Class of 2019 SAURABH ANNADATE ALICIA BURRIS ALEX BURZINSKI TED CARLSON IVAN CHEN ANGELA CHEN CARSON CHEN HARISH CHOCKALINGAM SABARISH CHOCKALINGAM TONY COLUCCI JD COOK SOPHIE DU JAMES FAN MICHAEL FEDELL JOYCE FENG NATHAN FRANKLIN TIAN FU ELLIOT GARDNER MAX HOLIBER NAOMI KADUWELA MATT KEHOE JOE KUPRESANIN MICHEL LEROY JONATHAN LEWYCKYJ Class of 2019 HENRY PARK KAREN QIAN FINN QIAO RACHEL ROSENBERG SHREYAS SABNIS SURABHI SETH TOVA SIMONSON MOLLY SROUR DHANSREE SURAJ TANYA TANDON KATIE TANG MARCUS THUILLIER SHIVA RAM VENKAT RAMANAN ARPAN VENUGOPAL ANJALI VERMA ZIYING WANG CLAUDIA XU NORA XU YIWEI ZHANG SHARON ZHANG EILEEN ZHANG YUCHENG ZHU SAURABH ANNADATE (773) 564-3568 | [email protected] | github.com/saurabhannadate93 Education Master of Science in Analytics, Northwestern University; GPA: 4.0/4.0 Sep 2018 – Dec 2019 • Coursework: Databases and Information Retrieval, Predictive Analytics (Supervised Learning), Data Mining (Unsupervised Learning, Recommender Systems), Big Data (Hadoop, MapReduce, Spark), Deep Learning, Data Visualization (D3 and Tableau), Text Analytics, Analytics Value Chain (Deployment, Cloud Computing) B.E. (Hons.) Mechanical Engineering, Birla Institute of Technology & Science, Pilani; GPA: 8.9/10.0 Aug 2011 – Jul 2015 Qualifications & Skills • Passed Level 1 CFA (Chartered Financial Analyst) exam in December 2016 • Languages and Tools: Python, R, SQL, Java, VBA, SAS, Hadoop, MapReduce, Spark, Git, AWS, D3.js, Tableau, Excel Professional Experience Data Science Intern, Capital One Jun 2019 – Aug 2019 • Built pipelines to test the utility of automated feature creation, feature selection and algorithm selection & optimization functionalities offered by AutoML tools like H2O driverless AI and DataRobot for credit card loss forecasting • Developed a POC for the model monitoring module of a credit card loan charge-off loss prediction model Analytics Consultant, Chicago Botanic Garden Feb 2019 – Jun 2019 • Developed a classification model for customer segmentation to inform marketing efforts using supervised machine learning techniques • Architected and built an end-to-end ML pipeline including a flask application and deployed the solution in an in-house Windows server Analytics Consultant, University of Chicago Urban Labs Crime Lab Oct 2018 – Jun 2019 • Explored architectures like GLMs, Neural Networks, Gradient Boosted Trees and ensemble models for modeling the propensity of an individual to be involved in a crime • Helped UChicago Crime Lab validate their own model and identify additional features that may add lift and help improving the accuracy Business Operations Associate Consultant, ZS Associates Pvt. Ltd. Jul 2015 – Jul 2018 Worked for Fortune 500 pharmaceutical companies across various workstreams such as Salesforce Incentive Compensation Plan Design and Administration, Salesforce Design Optimization, Salesforce Territory Alignment Operations, Customer Targeting and Segmentation, and Specialty Pharmacy Performance Analytics • Led a team of five associates on a large-scale Salesforce Incentive Compensation Operations project; responsible for planning and workload distribution, ensuring quality and timeliness of all deliverables and facilitating all oral and written communication • Successfully led the implementation of new IC plan changes including requirements gathering, implementation planning, POC evaluations, System Integration Testing, User Acceptance Testing and rollout • Reduced cycle time by 75% and substantially improved quality in a Salesforce Territory Alignment Operations project by building an operationally efficient ETL process using SAS and in-house tools • Analyzed transaction level Specialty Pharmacy sales data in SAS and created a dynamic excel dashboard to study and track Key Performance Indicators for Specialty Pharmacies; Information was used by the client for contract renewals • Applied regression modelling to quantify the impact of Salesforce Design change recommendations to maximize YoY sales growth Academic Projects House price prediction full stack app • Built a completely reproducible and modular machine learning app from proof of concept to production in Python, hosted on AWS EC2 with 82% ML model accuracy and stored customer logs in RDS MySQL database Handwritten Text Recognition Deep Learning Model • Built a model using CNN and bi-directional LSTM with a Beam Search decoder to recognize text in handwritten text images Customer Segmentation for a Daily Local Newspaper • Used k-means clustering for customer segmentation to drive personalized recommendations via newsletter for a daily local newspaper Venmo Transaction Clustering • Developed a clustering solution in Spark to cluster Venmo Transaction data using text based attributes Achievements • Among Top 4 finalists selected for panel presentation in Data Smackdown organized by ENOVA Feb 2019 • Secured Third place in TEC{H}ACK Hackathon organized by the Boston Consulting Group (BCG) Jan 2019 Alicia Burris (612)-229-0011 • [email protected] • www.linkedin.com/in/aliciaburris • Open to Relocation Seeking opportunities to leverage a data science academic degree with data engineering skills gained in industry. EDUCATION Northwestern University, McCormick School of Engineering Evanston, IL Master of Science in Analytics December 2019 • Coursework includes eight month practicum and three month capstone group projects with industry partners Oberlin College Oberlin, OH Bachelor of Arts in Mathematics, Minor in Hispanic Studies December 2014 • Four year John F. Oberlin Scholarship Recipient; a competitive merit based scholarship Online Coursework Deep Learning Specialization on Coursera January 2019 • Hyperparameter tuning, Regularization, Optimization, CNNs, ML Project Structures, Sequence Models TECHNICAL SKILLS • Languages: Java, Python, SQL, R, JavaScript, AngularJS, HTML, CSS, jQuery, JSON, D3 • Frameworks: Spark, Hadoop, Spring MVC, Swagger UI, Pandas, TensorFlow, Hive, HBase • Tools: GCP, AWS, Docker, Kubernetes, IntelliJ, PyCharm, Eclipse, Maven, Git, Postman, Subversion • Modeling Skills: Regression, clustering (k-means, partitioning), classification trees, recommendation systems, KNN, factor analysis, time series, markov chains, survival analysis, principal component analysis PROFESSIONAL EXPERIENCE Palo Alto Networks Santa Clara, CA Big Data Engineering Intern June - September 2019 • Provided backend support for an on-premise legacy application that is migrating into the cloud. • Developed a RESTful microservice application to expose the APIs running within cloud based containers. • Configured JWT authentication and HTTPS protocols to establish cloud security measures. Optum Technology Eden Prairie, MN Application Developer March 2015– August 2018 • Built configurable logic for clinical assessment functionality to be leveraged by behavioral health programs. • Automated daily reports on large scales of data to provide recommendations for a member’s plan of care. • Reduced server outages by finding excess web service calls, logging statements, and database transactions. • Optimized costly data refresh logic by identifying 50,000 records with a high likelihood of future activity. PROJECTS Blue Cross and Blue Shield of Illinois, Montana, New Mexico, Oklahoma and Texas Student Data Science Consultant October 2018- June 2019 • Built a recommendation system to deliver suggestions to members when searching for in-network providers. • Used clustering and collaborative filtering to serve predictions in real time within a flask web application. Toddler Screening for Autism Spectrum Disorder (ASD) April 2019- June 2019 • Developed a web application to identify patients with a high risk of ASD hosted in Amazon Web Services. Ann & Robert H. Lurie Children's Hospital of Chicago Student Data Science Consultant October 2018- May 2019 • Used spinal and chest surgery recovery data to recommend cost reduction strategies for pain management. • Presented findings to the hospital’s director of nursing research. Predictive Analytics for an online book retailer October 2018- December 2018 • Identified target customers for an advertising campaign and predicted purchase outcomes. Alex J. Burzinski [email protected] • www.linkedin.com/in/alex-burzinski-2a572097 • (920) 366-4710 EDUCATION Northwestern University Evanston, IL Master of Science, Analytics Expected Graduation 12/2019 • Current 3.94 GPA
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