ATS Score
78/100
Work Experience
75/100
Header
85/100
Profile
80/100
Projects
78/100
Education
0/100
Certifications
0/100
Skills
80/100
Add education details to provide foundational background and improve ATS completeness.
Include relevant certifications to validate skills and improve recruiter confidence.
Provide a phone number and fully qualified URLs in the header for better ATS and recruiter accessibility.
Standardize date and employment type formatting in work experience to enhance ATS parsing.
Incorporate soft skills and group technical skills by category for improved readability.
Strong technical expertise in machine learning frameworks and cloud deployment (TensorFlow, PyTorch, AWS, Azure).
Demonstrated ability to deliver measurable impact with quantifiable results in internships and projects.
Experience building end-to-end ML pipelines with version tracking and deployment.
Clear focus on AI-powered product development and full-stack capabilities, showing versatile skill set.
Work Experience
75%
Descriptions are detailed with strong use of action verbs and quantifiable results (e.g., 'reduced ETL time by 30%', 'achieving 92% accuracy').
Use consistent formatting for dates and employment type fields; currently, these fields are empty or inconsistent which may reduce ATS parsing accuracy.
Consider adding a brief company description or industry context for each employer to enhance recruiter understanding.
Separate technical skills/tools used per role in a distinct section or bulleted format to improve readability.
Header
85%
The header includes a clear professional headline with relevant keywords such as 'Machine Learning Engineer' and 'Full-Stack Developer' which improves ATS matching.
Add a phone number to enhance recruiter contact options and include a full LinkedIn URL (with https://) for better ATS parsing.
Profile
80%
The summary is concise and includes strong keywords relevant to machine learning and cloud technologies, aiding ATS and recruiter appeal.
Consider adding a brief objective or career goal to clarify candidate aspirations and tailor the profile to specific roles.
Include a few quantifiable achievements or metrics in the summary to immediately showcase impact.
Projects
78%
Projects are well described with clear technical details and outcomes, demonstrating practical application of skills.
Add technologies used for each project explicitly to improve keyword density and ATS recognition.
Include links to project repositories or demos if available to provide recruiters with direct evidence of work.
Education
0%
Section missing. Include education details such as degree, institution, dates, and relevant coursework to strengthen the resume.
Certifications
0%
Section missing. Adding relevant certifications (e.g., AWS Certified Machine Learning, TensorFlow Developer Certificate) would boost credibility and ATS ranking.
Skills
80%
The skills section is comprehensive, listing many relevant hard skills and tools, which is excellent for ATS keyword matching.
Add a soft skills subsection to demonstrate interpersonal and teamwork abilities valued by employers.
Group skills by category (e.g., Programming Languages, Frameworks, Cloud Platforms) for better clarity and scanning.