Ishan Islam

Long Island University, Brooklyn, NY

B.S. in Computer Science, Dec 2025

• GPA: 3.69/4.00
• Vice President of CS Club
• Vice President of Google Developer Group LIU
• Dean's List Student

Accenture | AI and Machine Learning Fellow

Aug 2025 – Dec 2025

• Contributed to a fake news classification project, developing NLP pipelines and deep learning models to detect misinformation across large-scale datasets
• Implement and fine-tune supervised learning models using scikit-learn, TensorFlow, and PyTorch, achieving measurable improvements in accuracy and precision.
• Design data visualization dashboards with Python and Tableau to communicate model insights and performance metrics to both technical and non-technical stakeholders
• Analyzed complex, unstructured datasets in a scientific-style workflow, using Python, Pandas, and ML models to derive insights and support decision-making
• Assist in optimizing end-to-end ML workflows, including data cleaning, model training, hyperparameter tuning, and deployment in test environments.
• Applied data analytics and statistical reasoning to classification, experimentation, and model evaluation, foundational skills used in scientific informatics

Break Through Tech | AI and Machine Learning Fellow

Jun 2025 - Present

• Collaborate in cross-functional teams to design and implement machine learning solutions addressing real-world data challenges.
• Conduct exploratory data analysis (EDA) to identify patterns, feature relationships, and potential predictive signals.
• Engineered structured features from raw datasets to improve model interpretability and performance.
• Build and evaluate supervised learning models using classification and regression techniques under industry mentorship.
• Present analytical findings and model insights to peers and industry professionals in structured technical reviews.
• Apply statistical reasoning and experimentation frameworks to evaluate model effectiveness and business relevance.

Long Island University | Techincal Assistant

September 2023 – Dec 2025

• Diagnosed and resolved technical issues on computers to ensure optimal performance.
• Coordinated with service providers to schedule equipment maintenance and repairs.
• Performed software updates on library computers and confirmed proper hardware functionality.

Long Island University | Google Developer Group Vice President

Sept 2024 - Dec 2025

• Streamlined student onboarding by automating email invitations through SMTP.
• Secured hundreds of dollars in scholarships from BWOSS for club members, enabling them to obtain Google Career Certificates at no cost
• Partnered with Major League Hacking to host successful hackathons with over 20 attendees.

Fake News Classification Model

Lead Data Scientist

• Developed text classification models using TF-IDF feature extraction and logistic regression.
• Preprocessed and vectorized large-scale news datasets for binary misinformation detection
• Evaluated model performance using precision, recall, and F1-score metrics.
• Demonstrated ability to extract structured insights from unstructured textual data.

Spotify Breakout Potential Analysis

Lead Data Scientist

• Demonstrated ability to extract structured insights from unstructured textual data.
• Applied logarithmic transformation and feature scaling to stabilize high-variance follower data.
• Implemented K-Means clustering to segment artists into emerging, established, and underperforming tiers.
• Interpreted segmentation results to simulate quantitative A&R-style talent discovery.

TikTok Video Classification

Lead Data Scientist

• Eliminated 100% of inaccuracies in media details through data cleaning with the Python data stack (Pandas and Numpy)
• Developed a classification model, using to predict whether TikTok video transcriptions were claims or opinions, based on text features
• Tuned hyperparameters for Random Forest and XGBoost classifiers using GridSearchCV, optimizing for recall
• Preprocessed text data by extracting numerical features using CountVectorizer.
• Evaluated model performance through classification reports, confusion matrices, and feature importance plots, achieving strong recall and precision.
• Evaluated model performance through classification reports, confusion matrices, and feature importance plots, achieving strong recall and precision.
• The final model was deployed on test data, where the Random Forest model provided key insights into feature importance.

Waze Regression Analysis

Lead Data Scientist

• Developed a logistic regression model to predict user churn based on driving behavior and app usage metrics
• Cleaned and processed the dataset by handling missing values, scaling features, and capping outliers.
• Through exploratory data analysis (EDA), including correlation heatmaps and descriptive statistics, I gained insights into the data.
• Built and optimized a logistic regression model, evaluating its performance with metrics like precision, recall, F1-score, and a confusion matrix
• Created visualizations to determine results

Lightning Strike Analysis and Geological Graphing

Lead Data Scientist

• Developed an interactive Tableau dashboard to analyze the frequency, intensity, and patterns of lightning strikes across various geographical regions
• Integrated geological maps to overlay environmental features such as elevation, vegetation, and proximity to water bodies, correlating them with lightning activity.
• Utilized advanced Tableau functionalities, including calculated fields, filters, and parameters, to enable real-time data exploration and hypothesis testing.
• Presented findings on lightning-prone areas, offering actionable insights for disaster preparedness and risk management strategies.