Machine Learning Data Scientist

Mohammad Naderi Dehkordi, Ph.D.

Data Scientist

Email: **********@*****.*** Phone: 717-***-**** LinkedIn: linkedin.com/in/mndehkordi PROFESSIONAL SUMMARY:

Results-oriented Data Scientist with a proven track record of driving data-driven decision-making and delivering impactful insights. Proficient in machine learning, statistical analysis, and data visualization. Effective communicator and team player with a talent for translating complex technical concepts into easily understandable insights for non-technical stakeholders. SKILLS:

- Machine Learning: Regression, Classification, Clustering, Neural Networks, XGBoost, Random Forest

- Programming: Python (NumPy, pandas, scikit-learn)

- Data Manipulation: SQL, Data Preprocessing, Feature Engineering

- Data Visualization: Matplotlib, Seaborn, Tableau

- Tools: Jupyter Notebook, VS Code

- Statistical Analysis: Hypothesis Testing, A/B Testing

- Leadership: Team Management, Mentoring, Collaboration PROFESSIONAL EXPERIENCE:

1. Goucher College Associate Professor of Computer Science Location: Towson, Maryland, United States Duration: June 2025 – Present

- Taught Introduction to Computer Science, with a primary emphasis on foundational programming concepts using the Python programming language.

- Taught the Introduction to Machine Learning course, guiding students through projects involving classification, regression, clustering, and association rule mining.

- Instructed Data Analytics for Sustainability, emphasizing both supervised and unsupervised machine learning algorithms and their applications in environmental and social contexts. 2. Dickinson College Visiting Assistant Professor of Computer Science Location: Carlisle, Pennsylvania, United States Duration: April 2022 – May 2025

- Taught Statistics and Machine Learning course focusing on supervised and unsupervised learning algorithms.

- Taught Topics in Data Mining which was mostly about applying association rules by considering privacy aspects.

- Taught Introduction to Computing which was mainly focused on Python programming language. 3. The Data Incubator Fellow of Data Incubator

Location: San Jose, California, United States Duration: May 2021 - November 2021

- Conducted exploratory data analysis on large datasets, uncovering key insights and patterns to guide business strategies.

- Developed and deployed machine learning models for demand forecasting, reducing inventory costs by 15%.

- Collaborated with domain experts to translate business problems into analytical solutions, ensuring alignment with company goals.

- Presented technical findings to non-technical audiences during company-wide meetings, enhancing cross-departmental communication.

3. Isfahan Science Technology Town Data Scientist Location: Isfahan, Iran Duration: April 2019 - March 2021

- Developed an XGBoost-based model to predict electricity consumption in Isfahan, achieving 92% accuracy using family demographic features

- Implemented feature engineering techniques, reducing model complexity by 30% while maintaining accuracy.

- Deployed the model with Flask API, enabling real-time predictions for over 500,000 households.

- Conducted A/B testing on energy-saving recommendations, reducing peak hour consumption by 15%. 4. Isfahan University of Medical Sciences Data Scientist Location: Isfahan, Iran Duration: November 2017 - February 2019

- Led a research project on predicting ischemic, hemorrhagic, and transient ischemic attack (TIA) strokes using ensemble learning methods.

- Developed a Random Forest model with 88% accuracy in early stroke detection, a 20% improvement over previous methods.

- Implemented SMOTE to address class imbalance, improving recall for minority classes by 35%.

- Used SHAP values to interpret model predictions, enhancing transparency for medical professionals.

- Reduced false positive rates by 40% through feature selection and hyperparameter tuning with cross- validation.

KEY ACHIEVEMENTS:

- Pioneered Advanced Predictive Models: Developed and deployed an XGBoost-based model that achieved 92% accuracy in predicting electricity consumption for over 500,000 households, significantly enhancing resource allocation and reducing peak hour consumption by 15%.

- Impactful Data Analysis and Business Strategy: Conducted extensive exploratory data analysis and developed machine learning models for demand forecasting at The Data Incubator, reducing inventory costs by 15% and effectively translating complex technical findings into strategic business solutions for non-technical stakeholders.

EDUCATION:

- Ph.D. in Data Science 2009 Azad University, Iran

- M.Sc. in Computer Science 2001 Azad University, Iran

- B.S. in Computer Science 1999 Isfahan University of Technology, Iran

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