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Muhammad Shoaib ChiplunkarMC
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Muhammad Shoaib Chiplunkar

@muhammad_shoaib

Motivated Data Science & Analytics fresher building predictive models and actionable dashboards.

India
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What I'm looking for

I’m looking to contribute to a data-driven organization where I can build end-to-end ML pipelines and BI dashboards, turn messy data into predictive insights, and grow by owning real-world problem solving.

I’m a motivated and detail-oriented Data Science & Analytics fresher with strong foundations in Python, machine learning, and statistical analysis. I’m passionate about uncovering meaningful patterns in data and building predictive models that drive business decisions.

I’ve worked on end-to-end ML project pipelines through academic projects, self-learning, and a freelance engagement. I developed a tablet dissolution time prediction model and delivered an interactive Streamlit web app that lets users get real-time predictions without coding, covering the full lifecycle from data pipeline to deployed UI.

I also build clear, decision-ready analytics in Power BI and SQL. From an IBM HR Analytics dashboard (using Power BI, DAX, and SQL) to mobile sales dashboards with dynamic slicers, I focus on transforming data into practical insights that teams can act on.

Experience

Work history, roles, and key accomplishments

IC

Freelance ML Engineer

Independent Client

Jan 2026 - Present (5 months)

Developed an end-to-end tablet dissolution time prediction model for a pharmaceutical client, engineering physicochemical features and delivering a regression model with R²=0.75 on held-out test data. Built and deployed an interactive Streamlit app enabling real-time predictions from tablet parameters, independently owning the full ML pipeline.

Education

Degrees, certifications, and relevant coursework

UM

University of Mumbai

Bachelor of Science, Information Technology

Grade: CGPA 8.73 / 10

Pursuing a B.Sc. in Information Technology at the University of Mumbai with an expected graduation of May 2025, maintaining a CGPA of 8.73/10.

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