report · Jul 31, 2026, 4:27 PM

top match score

best fit role

✦Your closest match

Data Scientist

Your resume aligns best with Data Scientist (94%), supported by clear evidence of python, sql, and statistics. With 13 skills detected, you have a broad technical base to build on. The most common gaps across roles are cloud deployment, docker, and javascript — improving these lifts several of your scores at once.

Data Scientist

94%

Data Analyst

79%

NLP Engineer

67%

13 skills extracted from the resume

pythondata structures & algorithmssqlpandasnumpymatplotlibdata cleaningdata visualizationstatisticsmachine learningscikit-learnnlpgit & github

resume snapshot

EDUCATION B.Sc. in Computer Science, 2021 - 2025. Coursework: machine learning, statistics, linear algebra, data structures, and databases. SKILLS Python, pandas, numpy, scikit-learn, machine learning, SQL, NLP (nltk, sentiment analysis), data cleaning, matplotlib, Git. PROJECTS …

best match

94%

Data Scientist

average score

53%

across 11 roles

skills found

via keyword + synonym rules

roles ≥ 50%

7/11

half credit or better

01Role-by-role breakdown

Every role, scored.

present (7)

pythonsqlstatisticsmachine learningscikit-learnpandasdata visualization

partial (1)

deep learning

missing (0)

none

Your strongest signals here are python, sql, statistics, and machine learning. The deep learning is only partially covered — a short, focused effort could close them quickly.

02readiness & rehearsal

Polish the document. Prep the answers.

ats readiness

Recruiter-scan fitness.

ats score

Well structured — scanners and recruiters will find what they need.

Adequate length

The resume looks very short — aim for one full page with clear sections.

Contact details present

Dedicated skills section

Education mentioned

Projects or experience

Quantified achievements

Strong action verbs

Start bullets with verbs like built, designed, implemented, or analyzed.

Skill keyword richness

interview prep

Rehearse for Data Scientist.

Questions drawn from your strongest and weakest signals — answer each out loud in under a minute.

1
Walk me through a project where you used python — what was the measurable outcome?
2
How did you learn sql, and how do you keep your knowledge of it current?
3
Which project on your resume best shows real-world impact, and how would you quantify it?
4
Where do you see the Data Scientist role evolving in the next two years, and how are you preparing?

03gap intelligence

Where the points are hiding.

coverage matrix

Every skill, every role.

presentpartialmissing

Data Scientist

94%

Data Analyst

79%

NLP Engineer

67%

Business Analyst

58%

QA / Test Engineer

58%

Data Engineer

57%

Machine Learning Engineer

57%

DevOps Engineer

36%

Full Stack Developer

36%

Backend Developer

29%

Frontend Developer

17%

highest impact

Skills that unlock the most.

Learning any of these raises several of your role scores at once.

rest api

lifts 5 roles

+81.9 pts

javascript

lifts 4 roles

+65.2 pts

docker

lifts 7 roles

+51.2 pts

cloud deployment

lifts 3 roles

+42.9 pts

typescript

lifts 2 roles

+36.7 pts

agile & scrum

lifts 2 roles

+33.3 pts

what-if simulator

Pick skills to learn. Watch scores rise.

Toggle the skills below to simulate how your matches would change once you have learned them — computed live by the same scoring rule.

your biggest gaps

projected top matches

Data Scientist

94%

Data Analyst

79%

NLP Engineer

67%

Business Analyst

58%

QA / Test Engineer

58%

Data Engineer

57%

Select a skill on the left to preview your improved scores.

04grow & improve

Actionable improvements.

smart suggestions

Ways to strengthen your resume.

Actionable improvements based on your content and target role.

Add stronger action verbs

Achievement

Start your bullet points with verbs like "built," "optimized," "deployed," or "led" instead of passive phrases like "was responsible for."

Quantify your achievements

Achievement

Add numbers to your accomplishments: "Processed 50k+ records" or "Improved load time by 40%" makes a stronger impression than vague descriptions.

Expand your resume content

Structure

Your resume seems very brief. Add more details about your projects, responsibilities, and achievements to fill at least one full page.

Add GitHub or portfolio links

Structure

Include links to your GitHub profile or portfolio website so recruiters can see your actual code and projects.

recommended certifications

Credentials that boost your profile.

Based on your skills and gaps — these certifications add credibility.

IBM Data Science Professional Certificate

intermediate

IBM (via Coursera)

Full data science pipeline from data collection to model deployment.

~200h

pythonmldata analysis

TensorFlow Developer Certificate

intermediate

Google

Demonstrate proficiency in building TensorFlow models for computer vision, NLP, and time series.

~100h

tensorflowdeep learningml

AWS Machine Learning Specialty

advanced

Amazon Web Services

Advanced certification for designing, implementing, and maintaining ML solutions on AWS.

~100h

mlawspython

Google Data Analytics Certificate

beginner

Google (via Coursera)

Comprehensive program covering data cleaning, analysis, and visualization with real-world projects.

~180h

data analysissqlexcel

keyword density

How often skills appear.

Frequently mentioned skills signal expertise — but balance is key.

machine learning

3× (2.7%)

scikit-learn

3× (2.7%)

data cleaning

2× (1.8%)

nlp

2× (1.8%)

python

1× (0.9%)

sql

1× (0.9%)

pandas

1× (0.9%)

numpy

1× (0.9%)

role fit spectrum

Your match across roles.

Data Scientist94%

Data Analyst79%

NLP Engineer67%

Business Analyst58%

QA / Test Engineer58%

Data Engineer57%

google xyz formula

Resume Bullet Point Optimizer

Transform ordinary duty statements into high-impact, ATS-optimized lines following the formula: Accomplished [X] as measured by [Y] by doing [Z].

Try weak sample:

0 characters

05Learning roadmap

Your next 5 weeks, planned.

plan for

Built from the missing and partial skills of Data Engineer(current match 57%)

week 1

Building ETL data pipelines

Write a small extract-transform-load script in Python: pull data from a public API or CSV, clean it, and store it in a database table. Keep steps in separate functions. You already have related foundations, so focus on closing the specific gap rather than starting from zero.

week 2

Distributed data with Spark

Follow the official Spark quickstart (PySpark works well) to load a dataset, run transformations, and aggregate results. Compare a Spark job with the same task in pandas. You already have related foundations, so focus on closing the specific gap rather than starting from zero.

week 3

Workflow orchestration with Airflow

Install Airflow locally using the official quickstart and write a small daily DAG with two or three tasks. Schedule your ETL script from the previous week inside it. You already have related foundations, so focus on closing the specific gap rather than starting from zero.

week 4

Docker container fundamentals

Work through the official Docker getting-started guide. Write a Dockerfile for one of your apps or APIs, build the image, and run it locally until it works end to end. You already have related foundations, so focus on closing the specific gap rather than starting from zero.

week 5

Cloud deployment basics

Deploy a small app or API on a free tier of any major cloud or hosting platform. Practice environment variables, logs, and adding a simple health-check endpoint.

Responsible AI note

This tool is for guidance and learning only. Match scores are estimates based on keyword overlap, not hiring decisions, and a missing keyword does not necessarily mean a missing ability. Please combine these results with human review by mentors, teachers, or recruiters.