Student

Saloni Mourya *******@***.***

Tempe, Arizona (***) 566–0710 www.linkedin.com/in/saloni-mourya https://github.com/SaloniMourya EDUCATION

Arizona State University, Tempe, AZ May 2025

Master of Science, Information Technology 3.96 GPA Relevant Coursework: Analyzing Big Data, Database management Systems, Data Visualization, Natural Language Processing Rajiv Gandhi Proudyogiki Vishwavidyalaya, India Aug 2017 – Jun 2021 Bachelor of Technology, Computer Science and Engineering 3.70 GPA Coursework: Data Structures & Algorithms, Object Oriented Programming, Python Programming, Machine Learning TECHNICAL SKILLS

• Languages: Python (NumPy, Pandas, Scikit-learn, Plotly, Matplotlib, Seaborn, SciPy, NLTK), JavaScript, SQL

• Visualization/Big Data Tools: Tableau, Power BI, Qlik Sense, Postgres, ETL Pipelines, Kibana

• Cloud Platform and Tools: Google Cloud Platform, Google Colab, Git, JIRA, Databricks

• Statistical Analysis: Regression analysis, Machine Learning models, Relational Database Design, Data Preprocessing, Data Interpretation and Forecasting, Data Warehousing

• Certifications: Google Cloud – Cloud Digital Leader, Tableau for Data Science – Udemy, Skillsoft Badges (Release & Sprint Planning, Agile Development – Scrum, Using Kanban in IT, Software Data Analysis – Project Management Metrics) PROFESSIONAL EXPERIENCE

Application Development Analyst Dec 2022 – Jul 2023 Accenture Pune, India

• Leveraged advanced Tableau functions and complex calculations to facilitate data-driven decision-making, enhancing strategic insights for banking operations and reducing report generation time by 40%

• Designed and implemented robust ETL pipelines using Python and SQL, automating data extraction, transformation, and loading processes into Tableau, resulting in a 50% increase in dashboard efficiency and performance

• Led an agile project to cut on-demand reporting by 25% by employing data modeling to create an aggregated dataset from disparate sources, decreasing manual reporting efforts by 35%

• Integrated machine learning models using TensorFlow to enhance error prediction accuracy by 15%, directly impacting user experience.

• Applied statistical analysis techniques such as regression and clustering to derive actionable insights for business decision-making and forecast user behavior trends, contributing to strategic decision-making processes Application Development Associate Oct 2021 – Dec 2022 Accenture Pune, India

• Employed Python for data wrangling & statistical analysis, improving web app development and user experience

• Boosted operational efficiency by 17% through optimized data collection and analytics, streamlining processes for over 150 datasets and increasing business value by 25%

• Analyzed vast, complex datasets through decision trees & causal inference in machine learning

• Reduced bug resolution time by 14% during critical releases through effective issue resolution & documentation, while utilizing data mining techniques for product analytics & improvement strategies PROJECT WORK

Predicting Customer Lifetime Value (link) Mar 2024 – Jun 2024

• Conducted EDA on the "Online Retail II" dataset from UCI to identify data patterns and relationships

• Applied machine learning algorithms including Linear Regression, Decision Trees, Random Forests, Gradient Boosting, and Neural Networks, achieving a quantitative performance measure with RMSE of 2777.33 using Decision Tree Regressor

• Utilized quantitative insights to optimize marketing strategies, enhancing customer retention and driving revenue growth for e- commerce businesses

• Demonstrated proficiency in translating quantitative findings into actionable insights, facilitating informed decision-making in dynamic market environments

Data Science Job Salaries Dashboard, Arizona State University (link) Feb 2024 – Apr 2024

• Developed an interactive Tableau dashboard using Kaggle dataset, analyzing salary distributions and job classifications in data science.

• Delivered actionable insights on geographic salary trends, aiding HR and Talent Management teams in strategic planning.

• Delivered insights on company size, geographic salary distributions, and global salary trends for data science roles, aiding strategic decision-making and talent management

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