ATS Score
85/100
Header
90/100
Certifications
70/100
Skills
90/100
Profile
88/100
Projects
80/100
Work Experience
82/100
Education
75/100
Add consistent date formatting and employment types in work experience for clarity and ATS parsing.
Include start dates and completion status for education and certifications to improve completeness.
Enhance project descriptions with business outcomes and provide links to portfolios or code repositories.
Group skills into categories and add soft skills to balance the technical focus.
Expand certifications section with issuing authorities and dates, and add brief descriptions.
Strong technical proficiency across a wide range of data science and machine learning tools and frameworks.
Quantified achievements in work experience demonstrating measurable business impact.
Clear and focused professional headline and summary that incorporate key industry terms.
Experience with cloud platforms and deployment tools, indicating readiness for production environments.
Header
90%
Header includes full name, professional headline with relevant keywords, and clear contact information, which aids ATS parsing.
Add a location with city and state explicitly in a single line to improve geo-targeting by ATS.
Consider including a professional title or certification acronyms after the name for added clarity.
Certifications
70%
Certifications listed are relevant and add credibility, especially cloud and data analytics credentials.
Include issuing authorities and dates awarded consistently for all certifications.
Add brief descriptions or skills gained for each certification to show their relevance.
Consider adding more industry-recognized certifications if available to strengthen this section.
Skills
90%
Comprehensive list of hard skills and tools relevant to data science and machine learning, optimized for ATS keyword scanning.
Consider grouping skills into categories (e.g., Programming Languages, Machine Learning Frameworks, Cloud Platforms) for easier readability.
Add some soft skills to balance technical expertise with interpersonal abilities.
Profile
88%
Summary is concise and includes strong keywords like 'predictive modeling', 'machine learning', and 'cloud platforms' that ATS systems look for.
Profile highlights quantify achievements and specify tools, which improves both ATS and recruiter appeal.
Consider adding a brief objective or value proposition statement to clarify career goals.
Projects
80%
Projects demonstrate application of advanced modeling techniques and deployment, which is valuable for technical roles.
Descriptions include technical details and metrics but could be enhanced by stating business impact or outcomes more explicitly.
Add dates or timeframes to projects to show recent activity and progression.
Include links to project repositories or demos to improve recruiter engagement.
Work Experience
82%
Descriptions include relevant technical skills, tools, and quantifiable impacts, enhancing ATS keyword matching and recruiter interest.
Use consistent formatting for dates (e.g., month and year) and consider adding employment types for clarity.
Some job descriptions could better highlight leadership or collaboration skills and business outcomes.
Add metrics consistently across all roles to demonstrate impact, e.g., 'improved model accuracy by X%' or 'reduced processing time by Y%'.
Education
75%
Education section includes prestigious institutions and relevant fields of study, which is positive for ATS and recruiters.
Missing start dates and GPA may reduce completeness; consider adding these details if available.
Clarify if ongoing programs or expected graduation dates to indicate current learning efforts.
Include any honors, awards, or relevant coursework explicitly to strengthen this section.