Rithani Rajeswari Selvaraj

San Francisco, California 716-***-**** adz6tx@r.postjobfree.com https://www.linkedin.com/in/rithaniselvaraj/ EDUCATION

University at Buffalo, The State University of New York Aug 2021 - Feb 2023 Master of Science in Engineering Science Data Science Relevant courses: Statistical Data Mining, Probability Theory, Data Models and Query Language, Machine Learning, Data Intensive Computing, Programming and Database Fundamentals Kumaraguru College of Technology, Anna University – India. Jul 2017 - Jun 2021 Bachelor of Engineering in Computer Science

Relevant courses: Data Structures, Design and Analysis of Algorithms, Software Engineering, Big Data, Cloud Computing TECHNICAL SKILLS

Languages and Tools: Python, R, SQL, ETL Pipelines, Scikit-Learn, SciPy, MySQL, MongoDB, Microsoft SQL Server, Jira Cloud Services: Microsoft Azure, AWS, Share Point

Data Visualization and Analysis: Tableau, Power BI, Advanced Excel, Seaborn, Matplotlib, Plotly Statistical Modeling: Statistical computing methods, A/B Testing, Exploratory Data Analysis, Feature Selection, Data Mining, Data Transformation, Data Cleaning

Machine Learning: Classification, Regression, Clustering, Random Forest, Predictive Modelling, Decision Trees, Generalized Linear Model

PROFESSIONAL EXPERIENCE

TCR., Weston, Connecticut Mar 2023 - Present

Data Analyst

• Employed Microsoft Azure services (Azure Monitor, Power BI, Azure AD) to develop and maintain real-time cybersecurity monitoring dashboards.

• Analyzed Auth0 log data, identifying and mitigating security threats, brute force attacks, resulting in a 30% decrease in incidents.

• Established an efficient data model, automated reporting using Power BI Dashboards, and applied SQL queries for data manipulation, reducing manual workload by 80%.

• Collaborated with cross-functional teams to streamline workflows, enhancing product impact by 70% and contributing to improved overall cybersecurity measures.

Tekion., San Francisco, California May 2022 - Aug 2022 Data Scientist, Intern

• Built an NLP pipeline using Python, seamlessly translating a complex business problem into a technical solution. Successfully mapped 80,000+ dealer repair order codes to normalized codes, decreasing manual work by 60%

• Worked on writing and optimizing complex SQL queries to extract and interpret 500+ dealers’ data, merging multiple data sources seamlessly.

• Generated models utilizing logistic regression as a foundation, incorporating advanced techniques - TF-IDF, cosine similarity, and word2vec. Achieved a model accuracy rate of 92% resulting in valuable similarity scores. Madura Creation Pvt. Ltd., Tamil Nadu, India Jun 2020 - Jul 2021 Business Analyst

• Utilized Microsoft Visio, Lucid chart, and use case diagrams to document business needs for inventory, sales, and customer service. Led Lean Six Sigma initiatives with Minitab and Trello resulting in a 30% increase in operational efficiency and a 15% reduction in overall costs. Implemented Agile methodologies to focus on project workflows.

• Produced Business Reports and Tableau dashboards to track key metrics, leading to a 20% improvement in sales conversion rates. Adapted Project Metrics to monitor and optimize inventory performance with advanced Excel functions, compressing carrying costs by 25%.

• Computed Python for market research, enhancing product offerings and contributing to a 10% revenue increase. PROJECT EXPERIENCE

Customer Churn Prediction (Python, Pandas, NumPy, Scikit-Learn) Feb 2022

• Led a 4-member team in establishing ML model for bank customer churn prediction, leveraged customer information and transaction data, applying SMOTE technique to address imbalanced data.

• Implemented and compared logistic regression, decision tree, random forest, and XGBoost for churn prediction, attaining 85% accuracy.

Movie Genre Prediction Engine (Hadoop, Map Reduce, Spark) Dec 2022

• Created a predictive analytics pipeline by applying Spark to forecast genres of a movie, with preprocessed plots using Spark NLP library and Spark ML, achieving a precision of 74%; Independently worked to further increase performance by incorporating feature engineering methods, resulting in a raised accuracy of 81%. Quantium Project (Python, SQL, A/B testing) Mar 2021

• Assessed extensive transactional and customer data across 3 regions using Python and SQL. Deployed hypothesis testing and regression, leading to a substantial projected 15% increase in revenue.

• Strategically fine-tuned A/B testing methodologies to evaluate store layout, product selection, pricing, and promotions. Tracked and measured critical metrics, including achieving a 15% projected revenue increase; Total sales revenue growth by 12%; Increased customer count by 10%; Grew average transactions per customer by 8%.

• Designed and accelerated a comprehensive Tableau dashboard to support commercial recommendations.

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