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AI Engineer with less than a year in Machine Learning, Generative AI & Data Analytics
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Assessing your cultural and operational fit
Enthusiastic and detail-oriented B.Tech Data Science graduate with hands-on experience in Machine Learning, Generative AI, and Data Analytics. Passionate about leveraging data-driven insights to solve real-world problems. Comfortable working across the full pipeline from data preparation to model building and deployment. Seeking an opportunity to apply analytical skills, statistical knowledge, and coding expertise in a dynamic environment.
D.Y. Patil Agriculture & Technical University
B.Tech · Data Science
August 1, 2022 – July 1, 2026
Genesis College
HSC
January 1, 2021 – January 1, 2022
Shri Nageshwar High School
SSC
January 1, 2019 – January 1, 2020
Futuremind InfoTech Solutions
Data Analyst Intern
July 1, 2025 – May 1, 2026
Navi Mumbai, Maharashtra, India
Multi-Agent Research AI System
June 26, 2026 – Present
Designed a multi-agent system for automated search, reading, and report generation. Built a structured pipeline for automated research tasks using LLMs. Improved output quality using prompt engineering and agent coordination techniques. Technologies / Tools Used : Python, LangChain, LLMs, Prompt Engineering, HuggingFace
Sales Analysis Dashboard
June 26, 2026 – Present
Built a SQL Server Data Mart and Power BI reporting solution for sales performance analysis. Performed data extraction, cleansing, transformation, and dimensional modeling. Developed interactive dashboards to analyze sales trends, product performance, customer segmentation, discounts, and regional sales. Improved decision-making through KPI monitoring, drill-down analysis, and automated reporting. Technologies / Tools Used : SQL Server, Power BI, DAX, Data Modeling
Crop Disease Prediction & Management System
June 26, 2026 – Present
Built an image-based crop disease detection model using CNN for accurate identification. Integrated weather data to improve prediction accuracy and contextual relevance. Applied Grad-CAM for model explainability and better visual understanding. Developed a Streamlit application for real-time use by end users. Technologies / Tools Used : Python, CNN, Streamlit, Grad-CAM
Finance AR Analytics Dashboard
June 26, 2026 – Present
Developed an Accounts Receivable analytics solution to monitor invoice status, overdue payments, customer ageing, and receivable performance. Designed interactive Power BI dashboards including Overview, Status, Customer Ageing, and Transaction Analysis reports. Created KPIs such as Total Invoices, Overdue Amount, Due Amount, DSO, Average Days to Settle, and Customer Ageing metrics. Built data models and DAX measures to analyze receivable trends, payment behavior, regional performance, and customer-level outstanding balances. Implemented drill-through reports, filters, and dynamic visualizations to support finance decision-making and collection management. Generated transaction-level insights for invoice tracking, dispute monitoring, and overdue payment analysis. Technologies / Tools Used : Power BI, SQL Server, Excel, DAX, Data Modeling
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in diverse applications of AI and data science, from crop disease prediction to multi-agent research systems and financial analytics. This breadth of interest, coupled with an internship experience, suggests adaptability and a willingness to explore different problem domains. The focus on data-driven insights aligns well with a culture that values analytical approaches and innovation. However, the experience is primarily academic, and further professional exposure would solidify cultural fit in a fast-paced industry setting.
Soft Skills & Operational Fit
The candidate lists problem-solving, analytical thinking, team collaboration, fast learning, and time management as soft skills. These are valuable for an AI Engineer role, indicating a proactive and collaborative mindset. The academic projects and internship show an ability to work on real-world datasets and contribute to development teams, suggesting a good operational fit for project-based work.