SAKSHI MEHTA

ad2dcd@r.postjobfree.com https://www.linkedin.com/in/sakshimehta27 https://github.com/sakshimehta99 +1-857-***-**** EDUCATION

Northeastern University, Boston, USA Jan 2022 – Dec 2023 Master of Science in Computer Science GPA:3.86/4

Related Courses: Probability Theory and Statistics, Data Mining, Predictive Analytics, Artificial Intelligence, Communication and Visualization, Business Intelligence, Risk Management and Leadership, Machine Learning, Database Management Systems Gujarat Technological University, Surat, India Aug 2017 – Jul 2021 Bachelor of Engineering in Computer Engineering GPA: 9.08/10 TECHNICAL SKILLS

Data Analytics and Visualization tools: Python, R, SQL, SAS, SAP, Pandas, NumPy, PyTorch, Matplotlib, Scikit Learn, TensorFlow, Keras, AWS, Microsoft Azure, Microsoft Office (Advanced Excel, Word, PowerPoint), Snowflake, Tableau, Microsoft Power BI, Alteryx, Qlik, R Shiny, MySQL, PostgreSQL, SQL Server, Oracle Statistical Modeling: Time-series forecasting, A/B Testing, Hypothesis Testing, Regression, Classification, ANOVA, Chi-square WORK EXPERIENCE

Data Analyst co-op Decibel Therapeutics, Boston, US Jan 2023 – Jul 2023

• Successfully performed data preprocessing including cleaning, standardization, and retrieval from the AWS S3 bucket by generating automated Python scripts, saving 2 hours per study.

• Analyzed the data and spearheaded statistical analysis in R (T-tests, Kruskal-Wallis) to extract insights on 28 viruses.

• Executed end-to-end ML pipeline from data preparation to deployment using SQL for efficient data querying, transformation, and integration with the ML workflow with 100% success.

• Created visualizations to illustrate viruses’ impact on positive hearing to cross-functional teams. (Seaborn, Matplotlib)

• Migrated all the existing Python scripts to GitHub using GitBash, improving work efficiency by 25%. Financial Data Analyst Intern Northeastern University, Boston, US Sept 2022 – Dec 2022

• Structured data and budget reports into detailed pivot tables using advanced MS Excel functions.

• Initiated data analysis techniques to analyze annual equipment charges, demonstrating proficiency in data collection and management for financial applications, boosting financial data accuracy by 23%.

• Automated invoice retrieval across multiple Excel sheets making it faster by 68%. (MACROS, XLOOKUP) Data Analyst Intern Nerdshouse Technology LLP, Surat, India Mar 2021 – Nov 2021

• Rectified client data discrepancies using SQL, saving 20 man-hours with an optimized workflow.

• Utilized Google Analytics for user engagement insights to provide website updates leading to an 18% customer growth.

• Sped up marketing strategy developments by 20% by creating dynamic PowerBI dashboards for tracking KPIs and bringing visibility to the performance metrics to stakeholders. ACADEMIC PROJECTS

End-to-end analysis of Uber’s data (Machine Learning, Python, Predictive Analytics)

• Explored Uber’s data and generated data visualization for the hourly traffic to estimate ride prices. (Plotly, NumPy)

• Carried out data wrangling, handled outliers (IQR method), and selected relevant features using a heatmap correlation.

• Applied ML data models(Linear regression, decision tree) for ride price prediction, elevating accuracy from 75% to 87%. Prescriptive Model for strategic decision-making (R Script, Microsoft Excel)

• Assessed and visualized product stock and sales, developed an inventory management system and statistical modeling in R, cutting down the paperwork by 75%. (ggplot2, Tidyverse, SCperf, Rmisc)

• Leveraged Excel Solver to determine Economic Order Quantity, significantly reducing material wastage. Exploratory Data Analysis-Kickstarter Dataset (Python, Tableau)

• Conducted EDA on 22k row Kickstarter dataset, employed data-driven methods to predict project outcomes with 93% accuracy based on 15 key features. (Pandas, Scikit-Learn)

• Devised interactive Tableau dashboard to forecast project success based on project length and launch year. Motor Vehicle Collision Analysis (Alteryx, PowerBI)

• Led NY Collision data staging, refining data quality by 18% with Alteryx by anomaly detection and data correction.

• Maintained efficient field mapping, cutting loading time by 30%, and implemented error handling for rejected rows.