Data Analyst with 2+ years in data analysis, automation & LLM integration.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Pritimukta Nanda is a Software Engineer with a Master of Computer Application. She has gained hands-on experience with SQL and Python for data analysis, automation, and improving data accuracy, streamlining data workflows, and creating Power BI dashboards. Her expertise includes exploring and integrating Large Language Models (LLMs) like Vertex for natural language processing. She also has experience in developing secure, high-performance financial web applications using Java and Python, engineering backend modules, and creating custom data visualization and financial reporting tools.
IMIT, Cuttack
Master of Computer Application
August 1, 2022 – June 30, 2024
Capgemini
Data Analyst
May 1, 2025 – Present
Pune, Maharashtra, India
Image InfoSystem Pvt. Ltd.
Software Programmer Trainee
April 1, 2024 – March 1, 2025
Delhi, Delhi, India
Cornerstone
June 1, 2026 – Present
Monitored and managed production jobs on AWS, ensuring smooth execution and timely issue resolution. Investigated and resolved job failures by analyzing logs, debugging errors, and implementing fixes. Performed negative scenario testing in AWS to validate system robustness and error handling. Identified and fixed issues in Power BI reports, improving data accuracy and dashboard performance.
FinWisely: AI-Powered Financial Advisor with Multi-Agent Systems
June 1, 2026 – Present
Developed a multi-agent AI platform using CrewAI and Google Gemini to automate comprehensive stock analysis (technical, fundamental, sentiment). Built custom tools for data extraction from Yahoo Finance, Reddit sentiment analysis, and news APIs, with SQL-like data processing in Python. Created interactive Streamlit dashboards with Plotly charts and PDF report generation for investment insights and decision-making. Leveraged Python, LangChain, pandas, and NumPy to orchestrate AI agents, enabling automated generation of detailed investment reports.
Introduction to LangGraph - Python
Foundation
June 1, 2026 – Present
Fundamentals Of Artificial Intelligence From NPTEL
NPTEL
June 1, 2026 – Present
Cloud Computing From NPTEL
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a blend of traditional data analysis (Cornerstone) and innovative AI/ML applications (FinWisely), suggesting adaptability and a willingness to explore new technologies. The experience in financial web applications and AI-powered financial tools indicates an interest in high-impact, data-driven domains. The breadth of tools and platforms used (AWS, Power BI, Streamlit, LangChain, LLMs) points to a versatile individual who can contribute to diverse technical environments. However, the limited professional experience (less than 2 years) might require mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to investigate and resolve issues, perform negative scenario testing, and streamline workflows, indicating problem-solving skills and a focus on operational efficiency. The FinWisely project highlights initiative and the ability to integrate complex AI systems.