Chandana Reddy Akkamma
@chandanareddyakkamma
Aspiring machine learning and data analytics engineer delivering end-to-end AI/ML solutions via REST APIs.
What I'm looking for
I’m an aspiring Artificial Intelligence and Data Analytics engineer with hands-on experience in Python-based machine learning, deep learning, and SQL-driven analytics. I focus on applying SDLC and agile practices to build, evaluate, and deploy AI/ML models through REST APIs, while turning insights into decision-ready dashboards using Power BI.
In my Data Science Intern role at Sharp Tech Systems Pvt. Ltd., I engineered end-to-end data preprocessing pipelines that reduced dataset preparation time by ~40%, and built Power BI dashboards that cut reporting turnaround by 2 days per sprint. I also prepared and validated structured datasets with SQL and Python to ensure zero null-value leakage and documented pipelines to improve reuse and clarity across the internship engagement.
Experience
Work history, roles, and key accomplishments
Data Science Intern
Sharp Tech Systems Pvt. Ltd.
Jun 2025 - Aug 2025 (2 months)
Built Python-based data preprocessing pipelines with Pandas/NumPy, cutting dataset preparation time by ~40% to support ML training and evaluation. Created Power BI dashboards for model performance metrics, reducing reporting turnaround by 2 days per sprint.
Education
Degrees, certifications, and relevant coursework
Jain Deemed-to-be University
Master of Computer Applications (MCA), Computer Applications
2024 -
Grade: SGPA: 9.29/10
Pursuing a Master of Computer Applications (MCA) at Jain Deemed-to-be University, Bengaluru (Aug 2024–present). Maintains SGPA of 9.29/10 with no active backlogs.
Kristu Jayanti Deemed-to-be University
Bachelor of Computer Applications (BCA), Computer Applications
2021 - 2024
Grade: CGPA: 9.35; First Class with Distinction
Completed a Bachelor of Computer Applications (BCA) at Kristu Jayanti Deemed-to-be University, Bengaluru (Sep 2021–Jun 2024). Earned CGPA of 9.35 with First Class with Distinction and secured above 60% throughout.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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