Pamela Austin

I'm a Data Analyst with deep experience delivering high-impact analytical solutions across marketing, telecom, retail, and finance, specializing in turning complex datasets into actionable insights that drive measurable business outcomes. You can check out my resume .

Expert in advanced analytics, AI, and ML applications, including predictive modelling, forecasting, anomaly detection, automated financial workflows, and end-to-end ETL pipeline design using Python, PySpark, SQL, Snowflake, AWS, and Databricks. Proven success leading large-scale data quality and optimization initiatives — deduplicated 150M+ records with zero data loss, engineered cloud pipelines delivering 87.5% faster processing and $250K annual savings, and built ML forecasting models achieving 94%+ accuracy with multimillion-dollar impact.

Skilled in developing interactive BI dashboards and data products using Power BI (DAX), Tableau, and Snowflake; improved dashboard performance by 25% through optimized data governance, modelling, and validation frameworks. Developed advanced Excel models and high-impact PowerPoint presentations translating complex analytical and financial insights into clear, actionable narratives for C-suite and non-technical stakeholders.

📊 Featured Projects:

My work portfolio showcases data solutions that have driven real business value:

💼 Professional Experience:

  • Syilum LLC – Freelance Business Intelligence Analyst (Oct 2025 – Present)
  • Signet Jewelers – Data Analyst (Jun 2025 – Sep 2025)
  • AT&T – Data Analyst – Senior (Mar 2024 – Mar 2025)
  • Syilum LLC – Product Data Analyst (Jan 2016 – Mar 2024)
  • Support Optics – Data Analyst (Jan 2013 – Jan 2016)

🎓 Education & Certifications:

  • B.S. Computer Science – National American University (2016)
  • A.S. Finance & Accounting – University of Phoenix (2011)
  • IBM – Database and SQL for Data Science with Python

Recent Work

Oct 2025 – Present Business Intelligence · Syilum LLC

📊 Syilum LLC – Product BI & Self-Service Analytics

Providing BI and analytics consulting for a technology company. Building Power BI dashboards tracking product KPIs (user engagement, feature adoption, retention) for executive stakeholders. Writing SQL queries analysing user behaviour patterns, conversion funnels, and feature usage to inform product roadmap priorities. Developed data quality validation frameworks ensuring 99%+ accuracy and self-service analytics solutions reducing ad-hoc report requests by 60%.

Power BI SQL Snowflake Python Data Quality Self-Service Analytics
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Jun 2025 – Sep 2025 Business Intelligence · Financial

💎 Signet Jewelers – M&A Financial Business Intelligence

Delivered BI and SQL analytics for Signet Jewelers' Corporate Development team supporting a $450M+ acquisition pipeline. Built Power BI dashboards with drill-through reports, RLS for 50+ stakeholders, and DAX measures for EBITDA and working capital analysis. Designed star schema (12 fact tables, 18 dimensions) and automated SQL reconciliation identifying $12.6M in accounting errors. Reduced financial consolidation from 6 weeks to 5 days (92% improvement) and improved dashboard performance by 65%.

Power BI DAX Advanced SQL Star Schema Snowflake Databricks Excel
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Mar 2024 – Mar 2025 Business Intelligence · AT&T

⚙️ AT&T – Business Intelligence & Self-Service Analytics Platform

Built AT&T Marketing Operations BI platform: 25+ Power BI dashboards for executive leadership tracking campaign performance, workforce costs, and budget allocations. Created self-service analytics enabling 150+ business users and reducing IT requests by 60%. Optimized dashboard query times from 45 seconds to 3 seconds (93% improvement) through data model optimization. Consolidated Workfront, Salesforce, and ZoomInfo into a unified Snowflake reporting layer.

Power BI DAX Tableau Snowflake Advanced SQL Dimensional Modeling Fivetran
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Mar 2024 – Mar 2025 Marketing Analytics · AT&T

📊 AT&T – Marketing Campaign Analytics & Reporting

Built unified marketing analytics reporting integrating Workfront, Salesforce, and ZoomInfo via Fivetran into Snowflake. Developed dashboards tracking 200+ concurrent campaigns with daily refresh, campaign attribution logic, and budget variance analysis. Enabled self-service analytics for 150+ users, reducing IT requests by 60% and manual data retrieval by 40%.

Power BI Snowflake Fivetran Salesforce Advanced SQL Tableau
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Mar 2024 – Mar 2025 Predictive Analytics · AT&T

📈 AT&T – Predictive Analytics & Operational Dashboards

Built predictive models forecasting project timelines and resource requirements across AT&T Marketing Operations, achieving 89% accuracy and reducing project overruns by 28%. AI-driven operational intelligence reduced escalations by 30%. Integrated forecasting outputs into Power BI operational dashboards enabling real-time visibility for 150+ marketing operations users.

Power BI Python Predictive Analytics Snowflake SQL scikit-learn
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Jan 2016 – Mar 2024 Business Intelligence · Syilum LLC

📱 Syilum LLC – Product & Marketing Business Intelligence

8+ year BI tenure building 100+ Power BI and Tableau dashboards tracking product metrics, marketing performance, and financial KPIs. Designed semantic layer enabling self-service analytics for 200+ users (60% IT reduction). Processed clickstream at 10M+ daily events; A/B testing drove 23% feature adoption increase; marketing analytics across 15+ channels improved efficiency by 22%.

Power BI Tableau Snowflake SQL A/B Testing Dimensional Modeling
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Jan 2013 – Jan 2016 Healthcare · Finance · BI

🏥 Support Optics – Finance, BI & Healthcare Analytics

Delivered actionable insights for clients across finance, business intelligence, and healthcare. Analyzed large healthcare datasets with full HIPAA compliance; developed predictive models forecasting healthcare outcomes; tracked HEDIS measures and CMS Star Ratings (3.5 → 4.2). Built interactive dashboards using Power BI, Tableau, and Excel. Performed statistical analysis including regression, hypothesis testing, and clustering to drive business strategy.

SQL Python Tableau Power BI HIPAA Predictive Analytics Statistical Modelling
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Nov 2025 Personal Passion Project

🌌 Exoplanet Habitability Analysis

Personal project: Comprehensive machine learning analysis of 5,000+ exoplanets to predict habitability and estimate life-supporting worlds in our galaxy. Built predictive models using Python scikit-learn and PySpark MLlib achieving 96.5% accuracy, with interactive visualizations and statistical extrapolation estimating ~300M potentially habitable planets in the Milky Way.

Python Machine Learning scikit-learn PySpark MLlib Pandas Seaborn
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