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AI Engineer with 2+ years in Data Analytics & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring AI/ML Engineer with hands-on experience in Python, SQL, Machine Learning, Deep Learning, Power BI, and Data Analytics. Skilled in data cleaning, exploratory data analysis (EDA), feature engineering, predictive modeling, and dashboard development. Experienced in building machine learning solutions and business intelligence dashboards through internships and projects. Passionate about leveraging data and AI to solve real-world business problems.
Nigama Engineering College Telangana
Bachelor of Technology (B.Tech) · Electrical and Electronics Engineering
N/A – June 30, 2025
Saiket Systems
Machine Learning Intern
May 1, 2026 – Present
India
Cognifyz Technologies
Data Science Intern
April 1, 2026 – May 1, 2026
India
Data Minds Analytics
Data Science intern
October 1, 2025 – March 1, 2026
India
Kotak Mahindra bank
Junior Associate
November 1, 2021 – January 1, 2023
India
E-commerce Sales & Customer Analysis Dashboard Using Power BI
June 23, 2026 – Present
Extracted actionable insights from 5000+ data rows using advanced SQL techniques and data analysis. Developed an interactive E-commerce Sales & Customer Analysis Dashboard with Power BI, driving 25% more informed data-driven decisions. Enhanced SQL data accuracy by 20% and reduced latency by 40% through Power Query and DAX optimization. Designed KPI dashboards with filters and slicers, driving 15% business growth through data-driven insights.
View ProjectAI-Powered Banking Customer Analytics Dashboard
June 23, 2026 – Present
Developed interactive analytics dashboard processing over 10,000 customer records, yielding actionable insights. Reduced churn rate by 25% through targeted customer segmentation and data-driven analysis. Enhanced business visibility by 30% with KPI dashboards for customer retention, empowering data-driven decision making. Boosted reporting efficiency by 35% with interactive dashboard visualization, reducing manual reporting time significantly. Increased customer lifetime value by 12% through data-driven customer engagement strategies and targeted marketing efforts.
View ProjectCredit Card Fraud Detection Using Machine Learning & Deep Learning
June 23, 2026 – Present
Developed a credit card fraud detection system using Machine Learning and Deep Learning techniques, achieving 95% model accuracy. Preprocessed 5 million transactions, enhancing model efficiency by 25% and handling imbalanced data effectively. Evaluated neural networks for fraud classification, achieving 12% higher precision and 15% fewer false negatives. Processed 1 million transactions per hour with minimal latency and throughput using Python, Scikit-learn, TensorFlow, Pandas, and NumPy.
View ProjectData Science & Analytics Training
Unknown
June 1, 2026 – Present
Machine Learning Using Python
Unknown
June 1, 2026 – Present
Introduction to MS Excel
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from e-commerce sales analysis to banking customer analytics and credit card fraud detection, indicates a broad interest in applying AI/ML across different domains. The internships in Data Science and Machine Learning align well with the target role of an AI Engineer, demonstrating a proactive approach to skill development and practical application. The listed soft skills also suggest a collaborative mindset, which is beneficial for team-oriented environments.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as communication, teamwork, problem-solving, analytical thinking, and attention to detail. These are crucial for an AI Engineer role, especially in collaborative environments and when translating complex technical concepts into business insights. The project descriptions indicate an ability to work with large datasets and deliver actionable results, suggesting a good operational fit for data-intensive roles.