Data Science with 1+ years in AI/ML modeling and data analytics.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine learning practitioner with hands-on experience building and evaluating predictive models using Python and scikit-learn. Strong foundation in feature engineering, statistical modeling, and model evaluation on real-world business datasets. Experienced in building reliable data preprocessing pipelines and translating structured data into actionable ML signals for trend analysis and anomaly detection.
Raghu Institute of Technology, JNTU-GV
B. Tech · Data Science
August 1, 2020 – June 30, 2024
Independent Analytics Consultant
Independent Analytics Consultant
February 1, 2025 – October 1, 2025
India
Global Expat Tax Consulting LLP (US Tax Filer)
Tax Analyst - Data & Coordination Support
December 1, 2024 – January 1, 2025
India
Shoonya Tax Solutions
Tax Analyst - Operations & Process Support
October 1, 2024 – November 1, 2024
India
Black Friday Sales Prediction – Research Project
June 1, 2026 – Present
Developed regression-based machine learning models to predict consumer purchase behavior during retail sale events Performed feature engineering including categorical encoding, normalization, and derived behavioral indicators Compared multiple models and evaluated performance using MAE, RMSE, and R2 metrics Conducted systematic hyperparameter tuning and cross-validation to improve model generalization
RoadSeva – AI-Powered Civic Tech Platform
June 1, 2026 – Present
Full-stack Road damage reporting & management system built for GVMC across 98 wards in Visakhapatnam. Designed and deployed end-to-end with zero infrastructure cost (Render + Groq free tiers), awaiting formal GVMC contract. Integrated Groq Llama 4 Scout vision AI for real-time photo-based road damage severity classification. Built multi-role access system (admin, commissioner, officer, field engineer, viewer) with GPS-tagged citizen grievance submission. Engineered ward-level Road Quality Index (RQI), route planning for field engineers, and public transparency dashboards. Implemented production-grade security: bcrypt password hashing, CSRF protection, login lockout, structured JSON audit trail. Stack: Fast API, Groq Llama 4 Scout, SQLite, Leaflet/OpenStreetMap, Chart.js, Jinja2, Python, HTML/CSS/JS
View ProjectAI Drift Monitor – Open-Source Risk Analytics System
June 1, 2026 – Present
Built automated Python pipelines to collect and process time-series data from public sources for longitudinal trend analysis Engineered feature extraction workflows to quantify shifts in sentiment and risk-related signals over time Implemented classification models and rule-based scoring mechanisms to track directional change in AI-related discourse Evaluated model performance using standard metrics and monitored metric drift across time windows Designed aggregated daily, weekly, and monthly indicators to support trend forecasting and anomaly-style monitoring
View ProjectGoogle Cloud Data Analytics Certificate
Google Cloud
June 1, 2026 – Present
Certificate of Appreciation IEEE SPS Treasurer; improved financial reporting efficiency by ~20%
IEEE SPS
June 1, 2026 – Present
AWS AI & ML Scholars
AWS
January 1, 2025 – Present
IEEE Leadership Summit 2023 — Presented on AI, ML, AR/VR, and emerging technologies to ~200 participants.
IEEE
January 1, 2023 – Present
Best Ambassador - Returning Mothers Conference 2023 (Community outreach & leadership).
Returning Mothers Conference
January 1, 2023 – Present
IEEE RMC 2023 Certificate of Achievement for emerging technology research idea.
IEEE
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including a civic tech platform and an open-source risk analytics system, indicates a broad interest in applying data science to various domains. Their involvement in IEEE and leadership roles suggests a willingness to engage with the community and share knowledge. The target role of Data Science aligns well with their academic background and technical projects. The contract roles as a Tax Analyst, while not directly data science, show adaptability and a structured approach to work. Overall, the candidate appears to be a good cultural fit for a role that values innovation, continuous learning, and practical application of skills.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative through personal projects like RoadSeva and AI Drift Monitor, indicating a proactive and self-driven work attitude. Their experience in tax analysis roles, while not directly technical, suggests an ability to handle structured data, follow processes, and ensure accuracy under deadlines, which are valuable operational skills. Leadership and communication skills are hinted at through IEEE presentations and ambassador roles. However, direct evidence of team collaboration and stress handling in a technical context is limited.