Aditya Pokharna

Business Analyst

Tempe, Arizona, United States0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Engineered AWS Athena integration for real-time analytics.
Developed predictive models with 88% accuracy.
Automated budget reporting, reducing effort by 50%.

Stackforce AI infers this person is a Data Science professional with expertise in SaaS and Healthcare applications.

Contact

pokharna.aditya91@gmail.com LinkedIn

Skills

Core Skills

Data AnalysisMachine LearningData VisualizationAnalyticsData EngineeringNatural Language Processing

Other Skills

AWS AthenaDjangoPostgreSQLReactPlotlyDashPower BIPower QueryAI-driven reconciliationETL pipelineRandom Foresttime-series ensemblePythonAWS S3Tableau

About

Master’s student in Data Science at ASU with experience in machine learning, data engineering, and full-stack development. Skilled in Python, SQL, C++, cloud computing, and AI frameworks. Passionate about LLMs, RAG, and data-driven decision-making. Always exploring innovative solutions at the intersection of AI and real-world applications.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Verde

Data Analyst

May 2025 – Present · 1 yr 1 mo · Phoenix, Arizona, United States · Hybrid

Engineered an AWS Athena integration to query, aggregate, and visualize multi-source operational and financial data for Hey Sage, Verde’s internal platform, enabling real-time analytics and eliminating manual data retrieval.
Developed and deployed REST APIs in Django connected to a PostgreSQL backend, powering React-based dashboards that improved accessibility and performance tracking for 250+ employees across operations, HR, and finance teams.
Built dynamic dashboards with Plotly, Dash, and Power BI, embedding them into the internal web interface to deliver interactive KPIs on safety, quality, customer engagement, employee participation, and financial performance.
Partnered with the COO and department heads to define and implement 15+ new KPIs, translating organizational goals into measurable metrics that enhanced cross-departmental decision-making and accountability.
Automated multi-source budget reporting using Power Query and AI-driven reconciliation, reducing manual reporting effort by 50% and cutting weekly turnaround time by 40%.
Designed a scalable ETL pipeline to standardize data inputs across multiple business locations, improving financial data accuracy to over 90% and ensuring reporting consistency enterprise-wide.
Implemented predictive models (Random Forest + time-series ensemble) to forecast weekly budget overruns with 88% accuracy, enabling proactive interventions and improving financial control.
Communicated analytical findings and presented process documentation and ROI analysis to the CFO and leadership.

AWS AthenaDjangoPostgreSQLReactPlotlyDash+8

Arizona state university

Graduate Student Assistant

Apr 2025 – Present · 1 yr 2 mos · Tempe, Arizona, United States

Techorbit solutions private limited

Data Analyst

Jul 2023 – Dec 2023 · 5 mos · Pune, Maharashtra, India · Hybrid

Built Python-driven ETL pipelines to automate SAP data archiving, processing 2M+ monthly records with AWS S3 integration, reducing data extraction latency by 15% and achieving a 99.8% long-term data retention rate.
Delivered 15+ client-facing Tableau dashboards tracking Key Performance Indicators like churn rate and sales growth, enhancing metric visibility by 30% and supporting decision-making for global clients.
Migrated datasets to AWS S3, reducing cloud storage retrieval latency by 30% and enabling scalable access for 10+ cross-functional teams. Managed data annotation, deployed REST APIs, and integrated them with current pipelines.
Developed time-series models (ARIMA, SARIMA, Prophet) to forecast demand trends and build revenue models, reducing stock outs by 20% and improving forecasting accuracy by 18%.

PythonAWS S3TableauARIMASARIMAProphet+2

Indus international fzc

Data Scientist

Jan 2023 – Mar 2023 · 2 mos · Sharjah Emirate, United Arab Emirates · Remote

Automated cost sheet processing with Excel macros, cutting manual effort by 15+ hours/week, and designed scalable data pipelines with Azure data factory to handle 100K+ daily transactions, demonstrating initiative and process ownership.
Streamlined SQL databases, enhancing cross-departmental data accessibility by 40%, and integrated resource allocation metrics into real-time Grafana dashboards, enabling faster inventory decision-making.
Built predictive models using operational data to forecast equipment failures, reducing downtime by 25% and improving supply chain efficiency by 18%, reflecting strong problem-solving under real-world constraints.

Excel macrosAzure data factorySQLGrafanaData EngineeringData Analysis

Pune institute of computer technology

2 roles

Research Intern

Sep 2022 – Nov 2022 · 2 mos · Pune, Maharashtra, India · On-site

Researched and developed a federated learning framework tailored for healthcare applications on the MIMIC‑III dataset, ensuring data privacy and security, achieving a 25% increase. Analyzed healthcare datasets and evaluated model performance.
Achieved comparable results in ML models trained in a federated environment to those trained on centralized data storage. Investigated technologies such as PySyft, TFF, and TensorIO in healthcare‑related machine learning applications

Research Intern

Apr 2022 – Jun 2022 · 2 mos · Pune, Maharashtra, India · On-site

Conducted web data scraping and preprocessing of business reviews and ratings. Utilized Topic Modeling (LDA, LSA) for review categorization and implemented advanced Natural Language Understanding models (RNNs, LSTMs, BERT) for sentiment analysis.
Developed a domain‑specific Named Entity Recognition (NER) method, enhancing data insights, and increasing entity extraction accuracy by 35%. Introduced a comprehensive metric for business comparative analysis, providing actionable data‑driven decision‑making tools.