Associate Consultant

Vibhas Goel

Boston, MA • 857-***-**** • *******@**.*** • linkedin.com/in/vibhasgoel/ • github.com/VibhasGoel1 SUMMARY

Detail oriented, experienced consultant with a keen sense of data and a good knack for providing data driven solutions who has handled multiple roles as project lead, team lead and developer. EDUCATION

M.S. Business Analytics (STEM)

Boston University Questrom School of Business, Boston, MA GPA: 3.78 Expected August 2023

Bachelor’s of Technology in Computer Science and Engineering April 2019

Vellore Institute of Technology; Vellore, India

Relevant Coursework: Machine Learning, Statistics, Data Analytics, Lean Startup Management, Supply Chain, A/B Testing SKILLS

SQL(A), Python(A), Power-BI(I), SSIS(A), Tableau(I), GCP(I), Google Analytics(F), PySpark(F), BigQuery(F), Azure Devops(I) WORK EXPERIENCE

Infosys Limited, Pune, India October 2021 - June 2022 Associate Consultant, Client: Microsoft

• Led cross-functional teams as the project lead, through all phases of project life cycle including R&D, requirement analysis, system design, business use case development, implementing corrective actions to keep project on track.

• Collaborated with functional team leads to understand business requirements and build a one fit model using SQL and PowerBI to automate and report monthly/quarterly data, providing business insights, increasing team efficiency by 15%.

• Piloted an Employee Utilization Metric model for all functional teams in the project and reported to client using PowerBI, LINQ, SQL Queries, Azure Devops and C# increasing employee utilization rate by 20%.

• Implemented CI/CD pipelines on Azure to automate UAT/PROD build, test and deployment processes resulting in a 33% reduction in release cycles and improved software quality. Wipro Limited, Hyderabad, India July 2019 - October 2021 Project Consultant, Client: Microsoft

• Collaborated with Project Managers, Business Partners, and Subject Matter Experts as a project analyst to develop and document use cases for software development using Agile framework, ensuring effective project execution.

• Transformed manual data gathering to automated ETL Transactions via SSIS Packages in SQL, decreasing time taken by 50%.

• Achieved zero-touch automation for mapping products with keys using stored procedures (SQL) increasing productivity by 10%.

• Created PowerBI and SSRS reports that informed client on key marketing metrics and performance measures identifying top performing products increasing month-on-month downloads by 5%.

• Monitored data flow from cross server platforms in MS-SQL conducting root cause analysis to identify bottlenecks and improve performance of data models and architecture decreasing server downtime by 30%. RELEVANT PROJECTS

Impact Consulting, USA (Pro-Bono Consulting) May 2022 - Present

• Conducted market research for an Indonesian plywood company to devise a go-to-market strategy in foreign markets.

• Developed competitive benchmarking studies, evaluating competitor product features, pricing strategies and marketing tactics. Minne Analytics Case Competition, USA February 2023 - March 2023

• Part of the award-winning team selected to represent BU at Minne Analytics Case competition.

• Accumulated baseball retro-sheet data, queried historical weather data via API, scraped web data for rankings, player performance to build various statistical models, predicted attendance for games in MLB 2023 season with a R2 score of 0.83.

• Performed feature engineering to add various features like all-star count, player weights according to performance, percentage of stadium filled, player and team performance statistics increasing variance described by model using Python.

• Provided an optimized MLB 2023 games schedule and several actionable insights to boost attendance and fan engagement. Humana Mays Healthcare Analytics Case Competition, USA September 2022 - October 2022

• Semi-finalist among the top 50 from the 850+ participants across the United States.

• Worked on 900K+ Humana’s client records, to predict which Medicare Insurance members could be housing insecure with an AUC-ROC score of 0.76 using XGboost classifier and identified key variables to provide data-driven strategic insights.

• Performed data cleaning, feature extraction and engineering to identify key variables increasing accuracy by 30% using Python. Level of Skill: (I)-Intermediate (A)- Advanced (F)- Foundational

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