Data Analyst in Training | Python, Power BI, SQL | Turning messy data into clear insights

Rohan Mehra

Professional Summary

Aspiring Data Analyst with hands-on experience in Python, Power BI, and SQL. Skilled at transforming complex datasets into actionable insights and visualizations. Passionate about leveraging analytical skills and data-driven storytelling to support business decision-making and improve operational performance.

Education

B.S. in Mechanical Engineering

University of Illinois Urbana-Champaign

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GPA: 3.65

High School Diploma

Lincoln High School, Urbana, IL

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Skills

Technical Skills

  • Python (Pandas, NumPy)
  • SQL
  • Power BI
  • Excel
  • Jupyter
  • Git
  • scikit-learn
  • Seaborn
  • Matplotlib
  • MySQL

Soft Skills

  • Communication
  • Problem Solving
  • Critical Thinking
  • Stakeholder Focus
Score
75/100
Certifications
0/100
Work Experience
0/100
Header
80/100
Education
70/100
Profile
78/100
Skills
85/100
Projects
88/100
Add work experience or internships to demonstrate real-world application and increase ATS keyword hits.
Include certifications to validate skills and improve recruiter confidence.
Standardize date formats and include project timelines for clarity and ATS optimization.
Enhance the profile summary with quantified achievements and integrate profile highlights more seamlessly.
Expand on soft skills with examples in projects or volunteer work.
Strong technical proficiency in Python, SQL, and Power BI with practical project experience.
Clear and quantifiable project descriptions demonstrating data analysis and visualization skills.
Good academic performance with a relevant STEM degree.
Effective communication and stakeholder-focused approach highlighted.

Certifications

0%
Section missing. Adding relevant certifications such as Microsoft Power BI, Google Data Analytics, or Python courses would greatly enhance credibility.
Include any ongoing or planned certifications to demonstrate commitment to professional development.

Work Experience

0%
Section missing. Include any internships, part-time roles, or relevant experience to demonstrate practical application of skills.
If no formal work experience, consider adding detailed project descriptions or volunteer work to compensate.
Highlight any responsibilities or results achieved in roles to improve recruiter interest and ATS keyword matches.

Header

80%
The header includes a clear and concise headline with relevant keywords like 'Data Analyst', 'Python', 'Power BI', and 'SQL' which are ATS-friendly.
Add a professional summary or objective immediately below the header to improve recruiter engagement and ATS parsing.
Include a complete mailing address or at least city and state consistently formatted to enhance location-based searches.

Education

70%
Education section is complete with degree, institution, dates, and GPA, which is good for an entry-level candidate.
Consider formatting dates consistently and adding relevant coursework or academic projects to strengthen alignment with data analytics roles.
High school details may be omitted or minimized unless specifically required.

Profile

78%
The summary effectively communicates aspirations and skills but could be strengthened by quantifying achievements or specifying tools used in projects.
Profile highlights are well structured but could be integrated into the summary or bulleted for better ATS parsing.
Consider adding a brief objective statement to clarify career goals for entry-level roles.

Skills

85%
Strong list of relevant hard skills including Python libraries, SQL, Power BI, and data visualization tools which align well with data analyst roles.
Soft skills are clearly stated but could be better integrated with examples or demonstrated within project descriptions to add impact.

Projects

88%
Projects are well-described with clear outcomes, use of tools, and quantifiable results, which is excellent for showcasing practical skills.
Use consistent formatting for dates and include project durations to improve ATS parsing and recruiter understanding.
Consider adding technologies used explicitly at the start of each project description for keyword optimization.
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