Data Analyst with 1+ years in AI Data Operations & Quality Assurance
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Assessing your cultural and operational fit
Detail-oriented professional with nearly 2 years of experience in AI data operations, specializing in AI model training, data validation, and quality assurance. Achieved 98.5% annotation accuracy while supporting Deep Learning and Machine Learning workflows. Certified in Microsoft Excel, SQL, and Power BI through Codebasics. Passionate about data analytics and seeking opportunities as a Data Analyst, AI Data Analyst, Reporting Analyst, or Business Analyst.
Northern Base AI Labs
Process Associate
June 1, 2026 – Present
India
Vision Group Retail Technologies
Process Associate
August 1, 2024 – June 1, 2026
India
Blinkit Sales Analysis Dashboard
June 22, 2026 – Present
Built an interactive sales dashboard to analyze business performance. Cleaned and transformed retail sales data using Excel and Power Query. Performed SQL analysis to identify sales trends and business insights. Designed KPI dashboards using Power BI and DAX.
Weed Identification in Vegetable Plantation Using Deep Learning
June 22, 2026 – Present
Developed a Deep Learning model for weed detection using image classification techniques. Improved crop monitoring through automated weed identification.
Power BI
Codebasics
February 1, 2026 – Present
Microsoft Excel
Codebasics
February 1, 2026 – Present
SQL
Codebasics
February 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including a personal sales analysis dashboard and an academic deep learning project, shows initiative and a broad interest in data-related fields. The experience as a Process Associate in AI labs indicates a structured work approach. The target role of Data Analyst aligns well with the demonstrated skills in data manipulation, visualization, and analysis, suggesting a good cultural fit for data-driven environments.
Soft Skills & Operational Fit
The candidate demonstrates attention to detail through achieving high annotation accuracy (98.5%) and maintaining data quality. Collaboration with internal teams is mentioned, indicating a team-oriented approach. The experience in AI model training and data validation aligns with operational roles requiring precision and quality control.