Data Scientist

Data Science & Research Phoenix, Arizona, United States

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Summary

Developed model for anomaly detection, resulting in a 20% reduction in false positives, improving data accuracy
Improved model monitoring reports through data visualization tools, resulting in a 30% reduction in manual effort
Developed sentiment analysis model with an 85% accuracy rate, enabling better understanding of customer feedback and driving product improvements
Enhanced data analysis accuracy by 25% through in-depth analysis using k-means clustering and silhouette analysis
Improved information precision 37% by extracting insights using topic modeling and named-entity recognition
Implemented a virtual assistant using spaCy, and Rasa framework, boosted customer satisfaction by 53%
Built logistic regression ML model to detect fraudulent transactions, reduced the financial losses by 17%
Analyzed confusion matrices and ROC curves to model, achieving 95% accuracy. Optimized fraud solutions and improved risk management by accurately identifying patterns and anomalies.
Implemented a data pipeline using Apache PySpark to extract and transform 93K customers data, resulting in 42% increase in credit card transactions
Developed 2,100 lines of SQL code in five hours, enhanced data processing speed on 10+M rows in Postgres database
Utilized Agile methodologies and JIRA to plan and track data science projects, resulting in a 20% increase in project efficiency and on-time delivery

Expectations

Seeking Machine Learning and Data Science roles (Open to Full time, Part-time & Contract). Authorized to work in US. Open to relocating anywhere within the US at my own expense. Available to join immediately