Data Science Intern | Python, SQL, ML Projects | Final Year B.Tech Student

Rahul Deshmukh

Professional Summary

Final year Production Engineering student at NIT Trichy with hands-on experience in data science and machine learning projects. Built and deployed predictive models using Python, FastAPI, and Azure. Skilled in data wrangling, EDA, ML pipelines, and automation. Looking for entry-level roles in data science, analytics, or machine learning.

Work Experience

Data Intern – Supply Chain Analytics at Emerson (EIMC)

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Built Power BI dashboards to monitor GR status and vendor KPIs. Automated data workflows using Microsoft Power Automate. Gained practical experience in business-facing analytics and reporting.

Education

B.Tech in Production Engineering

National Institute of Technology, Tiruchirappalli

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GPA: 8.54 / 10

CBSE (XII)

Alard Public School, Pune

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GPA: 91.4%

CBSE (X)

Podar International School, Pune

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GPA: 91%

Skills

Technical Skills

  • Python (NumPy, Pandas, Scikit-learn, TensorFlow, Matplotlib, Seaborn)
  • SQL

Certifications

Python Programming

Machine Learning for Engineering Applications

Data Analytics

Database Management

Industry 4.0

Score
78/100
Header
80/100
Skills
75/100
Projects
88/100
Profile
82/100
Work Experience
70/100
Education
85/100
Certifications
65/100
Enhance work experience details with quantifiable outcomes and clearer descriptions of impact.
Complete certification details with issuing organizations and award dates for ATS optimization.
Add and highlight soft skills and teamwork abilities in profile and skills sections.
Include links to project repositories or live demos to showcase practical work.
Standardize date formats and section formatting for consistency and ATS readability.
Strong technical skillset in Python, SQL, and machine learning frameworks with practical project experience.
Relevant internship experience applying data science to supply chain analytics with business impact.
Well-documented projects demonstrating deployment, automation, and advanced modeling techniques.
Good academic performance at a prestigious institution with consistent educational achievements.

Header

80%
Header includes key contact information and professional headline with relevant keywords like 'Data Science Intern' and technical skills.
Add a full location with state or region to improve geographic clarity for ATS and recruiters.
Use a professional email address domain if possible to boost credibility.

Skills

75%
Technical skills are well listed, including programming languages, ML libraries, and tools relevant to data science.
Separate soft skills explicitly and add examples such as communication or problem-solving to appeal to recruiters.
Consider grouping skills by category (e.g., Programming, Data Visualization, Cloud) for easier ATS parsing.
Add proficiency levels (e.g., intermediate, advanced) for key skills to provide clarity.

Projects

88%
Projects are highly relevant, technically detailed, and include performance metrics demonstrating impact.
Descriptions effectively highlight tools, models, deployment methods, and business value.
Add links to project repositories or demos if available to enhance credibility.
Use consistent verb tenses and bullet points for readability.

Profile

82%
Profile summary clearly states academic background, skills, and career goals aligned with data science roles.
Incorporate more quantitative achievements or specific impact metrics to strengthen the summary.
Consider adding a brief statement about soft skills or teamwork to show well-roundedness.

Work Experience

70%
Experience section includes a relevant internship with specific tools and outcomes, which is good for entry-level roles.
Expand on responsibilities and achievements with quantifiable results, e.g., how automation improved efficiency or KPIs.
Include consistent date formatting and more detail about the business context or scale of projects.
Add any other relevant part-time or project-based experience to demonstrate continuous engagement.

Education

85%
Strong academic background with a reputable engineering institute and good GPA scores.
Listing secondary education with percentages is good for early career candidates.
Add expected graduation month and year for clarity.
Consider mentioning relevant coursework or academic projects related to data science.

Certifications

65%
Certifications relevant to Python, ML, and data analytics demonstrate commitment to skill development.
Add issuing authorities and dates awarded to increase trustworthiness and ATS recognition.
Consider including certification IDs or URLs if available.
Limit to certifications that are well-known or add clear value to the target roles.
    Data Science Intern | Python, SQL, ML Projects | Final Year B.Tech Student | Rahul Deshmukh | Resume Template - Yotru