Harsha Surya Deep Attada
Data Analyst • Hyderabad • h**************@gmail.com • 756****858 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 1+ years of experience performing high-volume data review and labeling for Amazon Alexa ML pipelines. Strong practical experience in dataset validation, manual transcription, and maintaining content policy compliance, demonstrated by a sustained 99% data-integrity rate. Proficient in Python and SQL for analysis, and in Excel and Power BI for business reporting and dashboarding from hands-on retail and streaming analytics projects. Experienced in applying complex annotation guidelines to conversational and audio data to produce training-ready datasets for speech and language models. Skilled at documenting processes, resolving ambiguous guideline cases in daily reviews, and delivering QA-driven outputs used by ML training and moderation teams.
Technical Skills
Programming Language: Python,SQL
Databases: MySQL
Testing & QA: Quality Assurance
Data Analysis & Visualization: Power BI
Data Integration & ETL: Data Validation
Project Management & Collaboration: Agile
Process Modeling & Documentation: Process Documentation
Work Experience
AMAZON
Hyderabad
Machine Learning Data Associate II (Contract)
03/2025 – Present
Worked on Amazon Alexa conversational and audio datasets to produce labeled training data and ensure content policy compliance for voice assistant ML workflows.
- Categorized user-Alexa conversation records into 21 sensitivity labels to create structured training data for language models and policy enforcement.
- Transcribed and timestamped user audio interactions to generate high-fidelity speech training sets while ensuring fidelity to speaker intent and timestamps.
- Enforced complex annotation guidelines and performed multi-step validation to maintain a 99% data integrity rate across daily delivery targets.
- Clarified ambiguous content interpretations during daily team reviews and updated convention notes to improve cross-workflow labeling consistency.
- Reviewed flagged interactions under ASCI workflows and escalated confirmed policy violations to moderation pipelines for compliance review.
- Documented recurring annotation edge-cases and contributed to process updates that reduced annotation rework and improved batch throughput.
Projects
Blinkit Analytics Project
Tools Used: SQL, Python, Excel, Power BI
- Analyzed 8,500+ retail sales records using SQL to identify purchasing trends and outlet-level performance drivers.
- Cleaned and validated transactional datasets with Python routines and Excel checks to ensure accuracy for KPI calculations.
- Built interactive Power BI dashboards to visualize sales, item counts, and customer ratings across 50+ outlets for stakeholders.
- Identified that medium-sized outlets delivered ~15% higher sales, informing inventory and assortment decisions.
Netflix Data Analysis
Tools Used: MySQL, SQL
- Queried and segmented 10,000+ user viewing records in MySQL to analyze content engagement patterns by genre and time-window.
- Filtered viewing sessions to surface peak engagement hours and calculated user-preference splits, finding ~45% favor Drama and Thriller.
- Assessed subscription and retention trends to identify ~20% higher sign-ups during promotional periods for targeted campaigns.
Education
Raghu Engineering College
Bachelor of Technology - Computer Science and Engineering • 2020 – 2024
Certifications
Microsoft Certified: Generative AI Fundamentals — Microsoft
Data Analysis — Innomatics Research Labs
AWS Academy - Cloud Foundations — AWS Academy
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