Open to opportunities

Ishaaq MM

@ishaaq

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Data scientist skilled in ML pipelines, modelling, and deploying production-ready analytics solutions.

India

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What I'm looking for

I am seeking a role where I can apply and extend my ML and deployment skills on real-world problems, with mentorship, clear impact metrics, and opportunities to ship production models.

I am a data scientist with hands-on experience building end-to-end machine learning pipelines, from data acquisition and preprocessing to feature engineering, model development, evaluation and deployment. I have delivered projects including fraud detection, a depression indicator deep-learning app, insurance premium prediction on 1.2M records, and clickstream customer conversion analysis, improving model performance and deployment readiness.

My technical toolkit centers on Python, SQL, TensorFlow, scikit-learn, XGBoost, MLflow and Streamlit, plus cloud familiarity with OCI and AWS. I value reproducible workflows, experiment tracking and practical deployment, and I thrive on turning data into reliable, actionable models that drive measurable business impact.

Experience

Work history, roles, and key accomplishments

Data Science and Analytics Intern

Ovniq Technologies

Feb 2025 - May 2025 (3 months)

Engineered ML pipelines for fraud detection and capstone projects, improving workflow efficiency and ensuring reliable results; executed full project lifecycles from data acquisition to model evaluation.

Python Pandas scikit learn TensorFlow Model Evaluation Streamlit MLFlow

Artificial Intelligence Intern

Coincent.ai

Aug 2024 - Oct 2024 (2 months)

Developed news classification and chatbot applications and applied ML algorithms for regression, classification, and clustering as part of guided projects.

Python TensorFlow scikit learn NLP Classification Chatbot data preprocessing Git

Education

Degrees, certifications, and relevant coursework

Government College of Engineering, Tirunelveli

Bachelor of Engineering, Electronics and Communication

2021 - 2025

Grade: 7.3 / 10.0

Activities and societies: Worked on fraud detection and student placement eligibility apps, developed ML pipelines, participated in guided projects including news classification and chatbot development.

Bachelor of Engineering in Electronics and Communication completed with a GPA of 7.3/10.0; coursework and projects focused on machine learning and AI applications.