Electrical Engineer  Data Analyst | Power Systems Modeling  Grid Optimization

Jake Mitchell

Professional Summary

Electrical Engineer with strong expertise in power system modeling, grid optimization, and data-driven product analysis. Skilled in Python, SQL, and simulation tools to forecast demand and enhance grid resilience. Proven ability to lead data projects and collaborate across teams to improve system reliability and feature adoption.

Work Experience

Product Experience Analyst at US Mobile

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Built SQL dashboards to track product KPIs, reducing data lookup time by 17%. Created ETL pipelines and Python scripts for user behavior analysis and churn prediction. Led A/B testing, collaborating with engineers to improve feature adoption by 16%. Resolved customer-impacting issues, boosting system uptime and reliability. Clustered user segments with K-Means to identify high-value opportunities.

Academic Engineering Projects at University of Texas at Austin

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Developed a battery demand forecast model using Python, reducing peak load error by 21%. Simulated Texas grid with PSS/E under increasing DER integration, proposing cost-saving transmission upgrades. Modeled protection relay behavior with MATLAB to improve coordination and reduce fault impact radius by 40%. Utilized QGIS for congestion mapping and identified critical bottlenecks using 5+ years of SCADA data.

Education

Master of Engineering in Electrical and Computer Engineering

University of Texas at Austin

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Bachelor of Science in Electronics Engineering

University of Illinois Urbana-Champaign

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Skills

Technical Skills

  • Power system modeling
  • Load Flow Analysis
  • Short Circuit Analysis
  • Arc Flash Studies
  • Protection  Control Systems
  • Grid Coordination (NERC, DER)
  • Energy Forecasting
  • Python
  • SQL
  • MATLAB
  • Power BI
  • ETL Pipelines
  • Data Visualization

Soft Skills

  • Critical Thinking
  • Attention to Detail
  • Teamwork
  • Time Management
  • Communication
Score
85/100
Projects
70/100
Education
75/100
Profile
85/100
Certifications
0/100
Work Experience
80/100
Skills
88/100
Header
90/100
Add relevant certifications or licenses to validate technical expertise and increase ATS keyword hits.
Enhance education section with GPA, honors, or relevant coursework to provide deeper academic context.
Standardize date formatting across all sections for better ATS parsing and professional appearance.
Expand project descriptions to include specific technologies used and measurable outcomes.
Include a brief objective or profile highlights to clarify career goals and unique value proposition.
Strong integration of engineering and data analysis skills demonstrated through measurable project and work outcomes.
Clear use of quantifiable metrics to showcase impact in work experience.
Comprehensive and well-organized skills section covering technical tools and soft skills.
Professional online presence with LinkedIn and GitHub links included.

Projects

70%
Project description provides technical details and outcomes, demonstrating applied skills.
Including specific technologies used and measurable results in the project section would strengthen impact.
Consider formatting project dates consistently and linking projects to skills or work experience for coherence.

Education

75%
Degrees and institutions are properly listed with dates, but GPA and honors are missing which could add value.
Adding key coursework or relevant projects under education could enhance alignment with job requirements.

Profile

85%
Summary is concise and includes relevant keywords such as 'power system modeling', 'grid optimization', and 'Python'.
Consider adding a brief objective or profile highlights to emphasize unique value propositions and career goals.

Certifications

0%
Section missing - adding relevant certifications such as PE license, PMP, or industry software certifications would improve credibility.

Work Experience

80%
Descriptions include quantifiable achievements (e.g., 'reducing data lookup time by 17%', 'improve feature adoption by 16%'), which strengthen impact.
Job titles and companies are clearly stated, but formatting dates consistently (e.g., month-year) would improve ATS parsing.
Consider explicitly listing technologies and methodologies used per role to boost keyword matching.

Skills

88%
Skills section is comprehensive, covering hard skills, soft skills, and relevant tools, which aids both ATS and recruiter scanning.
Organizing skills into categories is effective; consider adding proficiency levels or certifications to further validate expertise.

Header

90%
Header includes full name, professional headline with keywords, and contact information clearly presented.
Adding a physical street address or ZIP code could improve location specificity for local job searches.