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Hrushikesh Gunjal

@hrushikeshgunjal

Aspiring AI & data science engineer skilled in ML, deep learning, and web development.

India
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What I'm looking for

I seek an early-career role in AI/ML or data science where I can apply end-to-end modeling, deepen deep-learning skills, and contribute to impactful projects within a collaborative, learning-focused team.

I am an aspiring artificial intelligence and data science engineer with hands-on experience building machine learning and deep learning solutions, and a background in web development from an internship at Code-soft. I focus on creating end-to-end pipelines, from data preprocessing to model deployment and result visualization.

My projects include customer churn prediction, cataract detection using VGG-19 with transfer learning, browser automation testing with Playwright, and house price prediction using regression and ensemble methods. I have achieved strong model performance (around 85% accuracy in several projects) and implemented practical tooling using Python, Keras, OpenCV, Playwright, and related libraries.

I complement technical skills with leadership experience as Treasurer of the ACM Club at DYPIEMR, managing finances and budgets for technical events, and I hold certifications in AI, machine learning, and data science that reinforce my applied knowledge and readiness to contribute to data-driven teams.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

DP

Dr. D Y Patil Institute of Management and Research, Akurdi, Pune

Bachelor of Engineering, Artificial Intelligence and Data Science

2021 -

Grade: CGPA 7.89

Pursuing B.E. in Artificial Intelligence and Data Science with a CGPA of 7.89.

JA

Jawahar Navodaya Vidyalaya Ahmednagar

Class 12th (CBSE), Higher Secondary (Science assumed)

2020 - 2021

Grade: 87%

Completed Class 12th (CBSE) with 87% marks.

JA

Jawahar Navodaya Vidyalaya Ahmednagar

Class 10th (CBSE), Secondary Education

2018 - 2019

Grade: 85%

Completed Class 10th (CBSE) with 85% marks.

Tech stack

Software and tools used professionally

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