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Data Analyst with less than a year in data analysis, machine learning, and business intelligence.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Recent B.Tech graduate in Information Technology (2025) with hands-on experience in data analysis, business intelligence, and machine learning fundamentals. Currently pursuing advanced Data Science training with practical exposure to data cleaning, exploratory data analysis, dashboard creation, and predictive analytics using Python, SQL, Excel, and Power BI. Passionate about transforming raw data into actionable insights and seeking an entry-level Data Analyst role.
Datamites
Data Science
August 1, 2025 – June 30, 2026
Amal Jyothi College of Engineering
B.Tech · Information Technology
August 1, 2021 – June 30, 2025
Sensor-Driven Landslide Detection System
June 21, 2026 – Present
Enhanced an IoT-based monitoring system using ESP32 and environmental sensors to detect potential landslide conditions. Collected and analyzed sensor data including soil moisture, rainfall, and environmental parameters. Implemented threshold-based alert mechanisms for early warning and risk monitoring. Contributed to system integration, testing, and real-time data monitoring. Technologies: ESP32, Arduino IDE, Environmental Sensors, IoT.
VARSH Waters – Water Delivery Management System
June 21, 2026 – Present
Developed a web-based platform to streamline water-can ordering and delivery operations. Designed responsive user interfaces for order management and tracking. Improved operational workflow through efficient order coordination and monitoring. Technologies: HTML, CSS, JavaScript.
IT Service Management (ITSM) Incident Analytics
June 21, 2026 – Present
Worked on an end-to-end ML project using 46,000+ IT incident records, covering priority prediction, incident forecasting, auto-tagging, and RFC failure prediction. Built classification models using Random Forest and SMOTE to handle imbalanced data, and developed an ARIMA forecasting model achieving ~11% MAPE. Handled full pipeline: MySQL data extraction, EDA, feature engineering, model building, and evaluation using Python.
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of interests, from IoT systems to web development and machine learning. The 'IT Service Management (ITSM) Incident Analytics' project aligns well with a data-driven problem-solving culture. The 'Sensor-Driven Landslide Detection System' shows an interest in applying data analysis to real-world, impactful problems. The 'VARSH Waters' project indicates an understanding of operational efficiency. The pursuit of a Data Science degree and training further reinforces a commitment to data-centric roles. However, the projects are all academic, which limits the assessment of cultural fit in a professional environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems (landslide detection, incident analytics) and contribute to system development. The focus on streamlining operations and improving workflows suggests a practical, problem-solving approach. However, without specific behavioral assessment data, it's difficult to fully assess stress handling, team collaboration, or other soft skills.