Machine Learning Engineer

********@*****.***

773-***-****

SKILLS

LANGUAGES

Passionate and results-

driven Junior Machine

Learning Engineer with a

proven track record in

developing and deploying

high-impact machine

learning models.

Demonstrated ability to

improve business outcomes

through data-driven

insights, effective

communication skills, and

collaboration with cross-

functional teams.

programming Languages :

Python, R, SQL

Machine Learning :

Regression, Classification,

Clustering, Neural

Networks, NLP

Frameworks & Libraries :

TensorFlow, Keras, Scikit-

learn, Pandas, NumPy

Data Visualization :

Matplotlib, Seaborn,

Tableau

Data Preprocessing : Data

Cleaning, Feature

Engineering, Data Scaling,

Imputation

Model Evaluation : Cross-

Validation, ROC Curve,

Confusion Matrix, pAUC

Jupyter Notebook, Git,

Docker

French Advanced .

Diploma in Advanced

French

French Advanced .

Diploma in Advanced

French

JUNIOR MACHINE LEARNING ENGINEER

zara

pervez

EXPERIENCE

JUNIOR MACHINE LEARNING ENGINEER

University of Kansas.

Reduced Downtime : Implemented a predictive maintenance system for manufacturing equipment, reducing unplanned downtime by 30%. Enhanced Model Performance : Conducted data preprocessing and feature engineering on time-series sensor data, resulting in a 25% improvement in model performance. Innovative Solutions : Developed and validated machine learning models using time-series analysis and anomaly detection techniques.

JUNIOR DATA SCIENTIST INTERN

RandTech Solutions.

Developed and optimized machine learning models for predicting customer churn, achieving an AUC ROC score of 0.87, leading to a 10% reduction in churn rate. Collaborated with cross-functional teams to analyze customer feedback, resulting in a 20% improvement in product features. Created interactive dashboards using Tableau to present insights to stakeholders, resulting in a 20% increase in customer satisfaction scores. Conducted feature engineering and data preprocessing, improving model accuracy by 15%.

DATA ANALYST INTERN

Saint Anthony Hospital.

Analyzed large datasets to identify trends and patterns, providing actionable insights that informed business strategies and resulted in a 15% increase in operational efficiency. Automated data cleaning processes using Python, reducing manual work by 50% and saving the company 100 hours of labor monthly. Assisted in the development of data visualization reports, enhancing data-driven decision-making processes.

EDUCATION

BACHELOR OF SCIENCE IN COMPUTER SCIENCE

SPECIALIZATION : MACHINE LEARNING

California Institute of Technology Caltech.

ASSOCIATE DEGREE IN COMPUTER SCIENCE

Oakton Community College.

PROJECTS

Diabetes Prediction Using Machine Learning

HYPERLINK "https://github.com/zaraprvz/Diabetes-Prediction-Capstone-Project" House Price Prediction

https://github.com/zaraprvz/Diabetes-Prediction-Capstone-Project Processing image data for deep learning

https://github.com/zaraprvz/Diabetes-Prediction-Capstone-Project Objective: Developed a machine learning model to predict the likelihood of diabetes in patients using the Diabetes dataset.

•

Exploratory Data Analysis (EDA): Conducted comprehensive EDA with visualizations and statistical analysis to identify patterns and correlations.

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Model Selection & Training: Experimented with algorithms including Logistic Regression, Decision Trees, Random Forest, and Gradient Boosting.

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Hyperparameter Tuning: Optimized model hyperparameters using Grid Search and Random Search.

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Model Evaluation: Assessed models using accuracy, precision, recall, F1-score, and AUC-ROC metrics.

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Results: Achieved a model accuracy of 85%, with significant improvements in precision and recall through feature engineering and hyperparameter tuning. Demonstrated the effectiveness of ensemble methods in improving predictive performance.

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Built a regression model to predict house prices based on features such as location, size, and amenities.

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• Python, Scikit-Learn, Pandas, Matplotlib.

• Achieved a high degree of accuracy, assisting real estate agents in pricing decisions Enhanced image data preprocessing pipeline to improve model accuracy and robustness in various computer vision tasks.

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achieved [specific outcome, e.g., 95% accuracy] on the validation set, improving baseline performance by [percentage, e.g., 10%].

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• E-commerce Recommendation System

Built a hybrid recommendation model combining collaborative filtering and content-based filtering, increasing average order value by 15%.

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