Data Scientist Science

SAKSHI PANDIT

Phone: +1-202-***-**** •******.******@***.*** •LinkedIn •Washington, DC

EDUCATION

The George Washington University Washington, DC

Master of Science (M.S.), Information Systems Technology May 2025

• Graduate Certificate in Artificial Intelligence. Savitribai Phule Pune University Maharashtra, India Bachelors of Engineering (B.E.), Computer Engineering June 2023 TECHNICAL SKILLS

Programming Languages Python, C, C++, C#, R, CSS, HTML, JavaScript, SQL. BI tools Tableau, Tableau Prep, Power BI, Microsoft Excel, Jet Brains, Agile development. Databases

Big Data Technologies

MySQL, SSMS, SSRS, Oracle Developer, MySQL Workbench. Hadoop, PySpsark, Hive

IDEs and Application server Microsoft Azure, Anaconda, Jupiter Notebook, Google Collab, Microsoft, Visual Studio, Azure ML Studio, Databricks.

Project Management Tools GitHub, API Design, Asana, Jira, JDKs, Agile, CI/CD, Distributed Systems, Scrum. AWS Technologies Redshift, AWS Glue, S3, Lambda

WORK EXPERIENCE

GEORGE WASHINGTON UNIVERSITY Washington, DC

Graduate Teaching Assistant September 2023 - Present

• Led lab sessions for 45+ students in the Database Application course, teaching essential SQL querying techniques and best practices for relational database management.

• Developed and executed hands-on exercises, guiding students in writing and optimizing complex SQL queries to enhance their data analysis skills and problem-solving abilities.

COGNIFRONT PVT. LTD Maharashtra, India

Data Analyst Intern January 2022 - February 2022

• Optimized ETL workflows to extract, preprocess, and transform raw data from the dataset using Python libraries (Pandas, NumPy), enhancing processing efficiency and improving data quality through encoding, handling missing data, and feature scaling.

• Engineered features to refine relevant attributes, reducing model bias and achieving 97.42% accuracy for the KNN model while improving the performance of other classifiers.

SPACE EVOLVE Maharashtra, India

Data Analyst and Project Management Intern October 2021 - December 2021

• Assisted project management in planning and executing architecture projects using Jira, ensuring deadlines were met and supporting risk assessment by identifying and mitigating potential issues.

• Developed and utilized a Tableau dashboard to monitor project budgets, expenditures, and deadlines, enhancing data-driven decision- making and operational efficiency.

PROJECTS

Transportation Data Science Project Python, Spatio-Temporal Analysis, Data Visualization, Critical Thinking

• Collaborated in a transportation data science project aimed at enhancing road safety for vulnerable road users, hosted by the Northeast Big Data Innovation Hub and U.S. Department of Transportation.

• Preprocessed and analyzed New York City OpenData transportation datasets to identify road safety patterns, focusing on vulnerable road users, and conducted ETL processes to ensure data readiness for analysis.

• Formulated a self-guided research question to guide road safety recommendations and created a virtual poster board to communicate findings and data-driven solutions to stakeholders. DeepRec: Deep Learning-Powered Product Recommendations (Amazon Sales Dataset) Python, Data modelling

• Developed a deep learning-based product recommendation engine using Amazon sales data, improving recommendation accuracy and user personalization beyond traditional collaborative filtering techniques.

• Implemented neural networks and transformers to analyze user reviews, preferences, and item similarities, achieving enhanced predictions for product recommendations.

• Improved the ETL pipeline, integrating multiple data sources and reducing processing time by 40%, enabling faster and more efficient product recommendations.

Riding Through Seasons: Analyzing Capital Bikeshare and Weather Dynamics Spark, Databricks, SQL

• Designed and implemented an ETL pipeline in Databricks, integrating 5.3M+ ride records with real-time weather data, ensuring data quality, completeness, and consistency for risk analysis.

• Analyzed weather impact on ridership by querying large datasets, identifying high-risk conditions, and informing dynamic pricing strategies that increased revenue potential by 20%.

• Developed KPIs and metrics to analyze weather impact on ride patterns, improving reporting accuracy and decision-making.

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