Mahesh Pittala
Professional Summary
Geospatial Data Analyst with 0 years of experience supporting data quality, map-based analysis, and analytics through internships and academic projects. Experienced validating 2,250+ government records using SOP-driven manual audits and achieving 98.9% validation accuracy for election datasets. Skilled in QGIS-based booth-wise mapping across 20 constituencies to convert tabular election data into geospatial insight. Built Power BI dashboards and Excel/DAX reporting to surface KPI and SLA metrics for operations stakeholders. Conducted exploratory analysis and built anomaly-detection models using Python, Pandas, and scikit-learn to flag exceptions. Performed security triage using Nmap, Wireshark, Burp Suite and OWASP ZAP during a cybersecurity internship. Delivers reproducible analysis and documented workflows via GitHub and Google Colab to support traceability and handover.
Technical Skills
Work Experience
- Performed manual audits on election datasets using SOPs and validation checklists, achieving 98.9% validation accuracy.
- Reviewed and corrected data across 2,250+ government records by applying structured exception-resolution workflows to critical fields.
- Plotted booth-wise election results into QGIS maps covering 20 constituencies to enable geographic analysis of voting distributions.
- Identified recurring error patterns from audit logs and redesigned validation steps to reduce repeat exceptions and clarify reviewer decisions.
- Maintained error logs and processing trackers in Excel and SQL to ensure full auditability and traceability of validations.
- Developed Python scripts to normalize address fields and auto-match geocoded locations, reducing manual reconciliation effort.
- Built interactive Power BI dashboards to track KPIs and SLA-style metrics for operations stakeholders and leadership reviews.
- Designed Excel and DAX measures with Power Query transformations to standardize and refresh daily productivity datasets.
- Created Pivot Tables and Excel dashboards to summarize agent performance and surface process bottlenecks for decision-makers.
- Conducted exploratory data analysis using SQL and Pandas in Google Colab to identify anomalies and data quality issues.
- Implemented data validation rules and exception reports to streamline issue escalation with the founder and mentors.
- Coordinated weekly stakeholder updates and delivered ad-hoc analyses to support operational decisions and prioritization.
- Led network and system investigations using Nmap and Wireshark to identify anomalous traffic and exposed hosts.
- Executed web application security scans with Burp Suite and OWASP ZAP, documenting vulnerabilities and severity levels.
- Authored remediation guidance and SOPs for triage processes to standardize volunteer responses and follow-up steps.
- Managed communications with stakeholders to validate findings and prioritize pragmatic fixes for implementers.
- Coordinated project timelines and tracked remediation progress using Excel trackers to ensure timely closure of issues.
- Presented final security assessment reports and recommended mitigation steps to technical implementers and project leads.
- Built anomaly-detection pipelines using Python and Pandas to preprocess large datasets for model training.
- Trained Random Forest classifiers on CICIDS-derived data and evaluated models using confusion matrix and classification reports.
- Implemented feature engineering and imbalance-handling workflows using NumPy and Pandas to improve model robustness.
- Validated model outputs and integrated explainability traces to aid investigators in interpreting flagged anomalies.
- Deployed evaluation notebooks and model artifacts to GitHub and Google Colab to ensure reproducibility and handover.
- Documented model design, hyperparameters, and test results to support knowledge transfer to analytics stakeholders.
Education
Certifications
Achievements
- Coordinator – Induction Programme — 2023: Managed end-to-end onboarding processes and documentation for 1,400+ students.
- NSS Volunteer: Contributed to rural community awareness drives and national-level campaigns.
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