4 answers
Ayush
Student
Patna, Bihar, India
1
Question
Asked
352 views
How do i get my resume shortlisted for an entry level Data Science role?
I graduated with a computer science engineering degree in July 2024. Please review my resume and how should i improve it to get shortlisted for data scientist roles as an entry level candidate. I am going to add a few more projects soon. Also suggest a few projects that would stand out.
Resume link: https://drive.google.com/file/d/15kuiqCqPn4g9iBC7CkVg-n-dmlpdZJ_E/view?usp=drivesdk
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4 answers
Hakeem Ola Saka
Freelancer
73
Answers
Maryland Heights, Missouri
Updated
Hakeem Ola’s Answer
1. Optimize for ATS (Applicant Tracking Systems)
Use relevant keywords from the job description (e.g., Python, SQL, machine learning, data visualization).
Use standard headers like Skills, Experience, and Education.
Avoid overly creative formats that might confuse the ATS.
2. Highlight Your Technical Skills
Create a dedicated Skills section. Include:
Programming: Python, R, SQL
Tools: Tableau, Power BI, Jupyter Notebook
Techniques: Machine Learning, Data Cleaning, Statistical Analysis
3. Showcase Relevant Projects
Include a Projects section with 2–3 detailed examples:
Title: E.g., "Customer Churn Prediction using Machine Learning."
Tech Stack: Mention tools and languages used.
Impact: Highlight outcomes like "Improved prediction accuracy by 20%."
If you lack projects, create them! Use platforms like Kaggle or GitHub.
4. Leverage Education and Certifications
List relevant coursework (e.g., Statistics, Data Structures, Machine Learning).
Mention certifications:
Google Data Analytics Professional Certificate
IBM Data Science Professional Certificate
Coursera or Udemy courses.
5. Include Internship or Freelance Work
Even if it’s not formal employment:
Internships: Highlight data-driven tasks.
Freelance: Mention analyzing datasets for personal or academic purposes.
6. Quantify Achievements
Use metrics to show impact. For example:
"Analyzed sales data, leading to a 15% increase in revenue."
"Reduced data processing time by 30% using optimized SQL queries."
7. Write a Customized Objective Statement
Make it specific to the role:
Example:
"Detail-oriented data science graduate skilled in Python, SQL, and machine learning, eager to apply analytical expertise to solve real-world business challenges."
8. Provide a GitHub/Portfolio Link
Include a link to:
GitHub: Showcase coding projects and notebooks.
Portfolio Website: Present projects with visuals and explanations.
9. Network Strategically
Use LinkedIn to connect with Data Science professionals.
Request informational interviews or ask for resume reviews.
Attend webinars, hackathons, and meetups to build connections.
10. Proofread and Keep It Concise
Limit your resume to one page.
Avoid typos and grammatical errors—these can make a poor impression.
Use relevant keywords from the job description (e.g., Python, SQL, machine learning, data visualization).
Use standard headers like Skills, Experience, and Education.
Avoid overly creative formats that might confuse the ATS.
2. Highlight Your Technical Skills
Create a dedicated Skills section. Include:
Programming: Python, R, SQL
Tools: Tableau, Power BI, Jupyter Notebook
Techniques: Machine Learning, Data Cleaning, Statistical Analysis
3. Showcase Relevant Projects
Include a Projects section with 2–3 detailed examples:
Title: E.g., "Customer Churn Prediction using Machine Learning."
Tech Stack: Mention tools and languages used.
Impact: Highlight outcomes like "Improved prediction accuracy by 20%."
If you lack projects, create them! Use platforms like Kaggle or GitHub.
4. Leverage Education and Certifications
List relevant coursework (e.g., Statistics, Data Structures, Machine Learning).
Mention certifications:
Google Data Analytics Professional Certificate
IBM Data Science Professional Certificate
Coursera or Udemy courses.
5. Include Internship or Freelance Work
Even if it’s not formal employment:
Internships: Highlight data-driven tasks.
Freelance: Mention analyzing datasets for personal or academic purposes.
6. Quantify Achievements
Use metrics to show impact. For example:
"Analyzed sales data, leading to a 15% increase in revenue."
"Reduced data processing time by 30% using optimized SQL queries."
7. Write a Customized Objective Statement
Make it specific to the role:
Example:
"Detail-oriented data science graduate skilled in Python, SQL, and machine learning, eager to apply analytical expertise to solve real-world business challenges."
8. Provide a GitHub/Portfolio Link
Include a link to:
GitHub: Showcase coding projects and notebooks.
Portfolio Website: Present projects with visuals and explanations.
9. Network Strategically
Use LinkedIn to connect with Data Science professionals.
Request informational interviews or ask for resume reviews.
Attend webinars, hackathons, and meetups to build connections.
10. Proofread and Keep It Concise
Limit your resume to one page.
Avoid typos and grammatical errors—these can make a poor impression.
Iryna Tam
Writer, copywriter
188
Answers
Hagerstown, Maryland
Updated
Iryna’s Answer
Hello!
To get shortlisted for an entry-level data science role, your resume should highlight relevant skills, projects, coursework, and any experience related to data analysis, programming, and statistics. Below is a sample resume tailored for an entry-level data science candidate who graduated with a degree in computer engineering.
Sample Resume for Entry-Level Data Scientist
[Your Name]
[Your Address]
[City, State, Zip]
[Your Phone Number]
[Your Email Address]
[LinkedIn Profile]
[GitHub Profile]
---
### Objective
Motivated and detail-oriented computer engineering graduate with a strong foundation in data analysis, machine learning, and programming. Seeking an entry-level data scientist position to leverage analytical skills and technical knowledge to contribute to data-driven decision-making.
### Education
**Bachelor of Science in Computer Engineering**
University of [Your University], [City, State]
Graduated: July 2024
- Relevant Coursework: Data Structures, Algorithms, Machine Learning, Database Management Systems, Statistical Analysis, Data Mining
### Skills
- **Programming Languages**: Python, R, SQL
- **Data Analysis**: Pandas, NumPy, Matplotlib, Seaborn
- **Machine Learning**: Scikit-learn, TensorFlow, Keras
- **Database Technologies**: MySQL, PostgreSQL, MongoDB
- **Data Visualization**: Tableau, Power BI
- **Tools and Technologies**: Jupyter Notebook, Git, GitHub
- **Statistical Analysis**: Hypothesis testing, regression analysis
### Projects
**1. Predictive Modeling for House Prices**
- Developed a machine learning model using Python to predict house prices based on various factors using regression techniques.
- Utilized Pandas for data manipulation and Seaborn for data visualization.
**2. Exploratory Data Analysis on COVID-19 Dataset**
- Conducted a comprehensive analysis of COVID-19 data, identifying trends and patterns using Pandas and Matplotlib.
- Created visualizations to communicate insights effectively.
**3. Movie Recommendation System**
- Built a collaborative filtering-based recommendation system using R.
- Implemented user-based and item-based filtering techniques to recommend movies based on user's past ratings.
### Experience
**Data Science Intern**
[Company Name], [City, State] (Remote)
May 2024 - Present
- Assisted in data cleaning and preprocessing for large datasets in Python.
- Collaborated with the data science team to develop predictive models for customer segmentation.
**Research Assistant**
University of [Your University], [City, State]
September 2023 - June 2024
- Assisted in research projects involving data collection, analysis, and visualization using R.
- Participated in data interpretation and presented findings to faculty members.
### Extracurricular Activities
- **Member, Data Science Club**, University of [Your University]
Collaborated on projects and participated in hackathons and workshops focusing on data science techniques and tools.
- **Volunteer, Code for Good**
Contributed to local nonprofits by developing data-driven solutions to optimize their operations.
### Certifications
- **IBM Data Science Professional Certificate** (Coursera)
- **Google Data Analytics Professional Certificate** (Coursera)
---
### References
Available upon request.
Tips for Customizing Your Resume
Tailor Your Objective: Customize the objective statement to reflect the specific company or role you are applying for.
Quantify Achievements: Where possible, quantify your project outcomes or contributions to emphasize the impact of your work.
Highlight Relevant Projects: Include any data-related projects, even if they were part of coursework or self-initiated. Focus on those that illustrate your technical and analytical skills.
Keep It Concise: Aim for a one-page resume, especially for entry-level positions. Make every word count.
Format: Choose a clean, professional format. Use bullet points for easy readability.
By presenting your skills and experiences effectively, you can improve your chances of getting shortlisted for an entry-level data scientist role. Good luck!
To get shortlisted for an entry-level data science role, your resume should highlight relevant skills, projects, coursework, and any experience related to data analysis, programming, and statistics. Below is a sample resume tailored for an entry-level data science candidate who graduated with a degree in computer engineering.
Sample Resume for Entry-Level Data Scientist
[Your Name]
[Your Address]
[City, State, Zip]
[Your Phone Number]
[Your Email Address]
[LinkedIn Profile]
[GitHub Profile]
---
### Objective
Motivated and detail-oriented computer engineering graduate with a strong foundation in data analysis, machine learning, and programming. Seeking an entry-level data scientist position to leverage analytical skills and technical knowledge to contribute to data-driven decision-making.
### Education
**Bachelor of Science in Computer Engineering**
University of [Your University], [City, State]
Graduated: July 2024
- Relevant Coursework: Data Structures, Algorithms, Machine Learning, Database Management Systems, Statistical Analysis, Data Mining
### Skills
- **Programming Languages**: Python, R, SQL
- **Data Analysis**: Pandas, NumPy, Matplotlib, Seaborn
- **Machine Learning**: Scikit-learn, TensorFlow, Keras
- **Database Technologies**: MySQL, PostgreSQL, MongoDB
- **Data Visualization**: Tableau, Power BI
- **Tools and Technologies**: Jupyter Notebook, Git, GitHub
- **Statistical Analysis**: Hypothesis testing, regression analysis
### Projects
**1. Predictive Modeling for House Prices**
- Developed a machine learning model using Python to predict house prices based on various factors using regression techniques.
- Utilized Pandas for data manipulation and Seaborn for data visualization.
**2. Exploratory Data Analysis on COVID-19 Dataset**
- Conducted a comprehensive analysis of COVID-19 data, identifying trends and patterns using Pandas and Matplotlib.
- Created visualizations to communicate insights effectively.
**3. Movie Recommendation System**
- Built a collaborative filtering-based recommendation system using R.
- Implemented user-based and item-based filtering techniques to recommend movies based on user's past ratings.
### Experience
**Data Science Intern**
[Company Name], [City, State] (Remote)
May 2024 - Present
- Assisted in data cleaning and preprocessing for large datasets in Python.
- Collaborated with the data science team to develop predictive models for customer segmentation.
**Research Assistant**
University of [Your University], [City, State]
September 2023 - June 2024
- Assisted in research projects involving data collection, analysis, and visualization using R.
- Participated in data interpretation and presented findings to faculty members.
### Extracurricular Activities
- **Member, Data Science Club**, University of [Your University]
Collaborated on projects and participated in hackathons and workshops focusing on data science techniques and tools.
- **Volunteer, Code for Good**
Contributed to local nonprofits by developing data-driven solutions to optimize their operations.
### Certifications
- **IBM Data Science Professional Certificate** (Coursera)
- **Google Data Analytics Professional Certificate** (Coursera)
---
### References
Available upon request.
Tips for Customizing Your Resume
Tailor Your Objective: Customize the objective statement to reflect the specific company or role you are applying for.
Quantify Achievements: Where possible, quantify your project outcomes or contributions to emphasize the impact of your work.
Highlight Relevant Projects: Include any data-related projects, even if they were part of coursework or self-initiated. Focus on those that illustrate your technical and analytical skills.
Keep It Concise: Aim for a one-page resume, especially for entry-level positions. Make every word count.
Format: Choose a clean, professional format. Use bullet points for easy readability.
By presenting your skills and experiences effectively, you can improve your chances of getting shortlisted for an entry-level data scientist role. Good luck!
Thank you so much for the advice Iryna. This really helps. This gave me an idea about how I should rewrite my bullet points.
Also I have a google drive link of my resume attached in the question above. If you could review that it would be of great help to me.
Ayush
Brooke Jones
Product Management
31
Answers
Austin, Texas
Updated
Brooke’s Answer
To get your resume shortlisted for an entry-level data science role, focus on showcasing relevant skills such as Python, R, SQL, data visualization, and basic machine learning. Highlight academic or personal projects where you analyzed data, built predictive models, or created dashboards, and briefly describe the tools and results. If you’ve gained practical experience through internships, research, or hackathons, be sure to include those, as they demonstrate hands-on knowledge. Even school projects could help in showcasing the skills you have. Tailor your resume for each job by using keywords from the job description to align with employer needs and improve your chances of your resume getting through the application scanning process.
Certifications like Google Data Analytics or IBM Data Science can also help demonstrate your initiative and technical knowledge. Networking is key—attend career fairs, connect with alumni or professionals on LinkedIn, and seek referrals to stand out. By focusing on relevant skills, experience, and strategic applications, you can significantly improve your chances of getting noticed.
Certifications like Google Data Analytics or IBM Data Science can also help demonstrate your initiative and technical knowledge. Networking is key—attend career fairs, connect with alumni or professionals on LinkedIn, and seek referrals to stand out. By focusing on relevant skills, experience, and strategic applications, you can significantly improve your chances of getting noticed.
Danny Siegel
Management Consultant
4
Answers
Scarsdale, New York
Updated
Danny’s Answer
Hi Ayush, You actually have some rally great foundational skills, so you just need to reshape your resume to speak to business folks looking for your skillset. The format suggested from a prior commenter here seems fine, but here's some suggestions that will help get the attention of hiring manager: First, I would remove the Coursera stuff at the bottom...anyone can take those courses, so probably not worth mentioning, especially in contrast to your degree and really great research project experience. Second, you need to recast your research project into a problem/action/result framework...what problem(or hypothesis in an academic situation) were you trying to solve or explore? what did you actually do (including languages/data sets/process narrative)j? what resulted (preferably not in a statistical context...HR people assessing your resume won't know what you're talking about...so something more like "resulting model exceeded commercially available models for wheat yields by 15%"...obviously this will take some research, but it needs to give the reader an understandable measure of 'so what'). Third, I would make sure to include experience/expertise with compute, so like Azure/AWS/GCP knowledge and how you used them in the context of your project (so demonstrating that you have a foundational understanding of how to provision your own compute cluster with base packages for your development, storage, deployment from a repo, etc...basic code management). Finally, you mention soft skills, but you really don't have anything reflecting that in your experience...do you participate in leadership on any academic clubs? are you part of any industry organizations? did you present your research to any large groups? You’ll need something to substantiate the assertion that you can communicate well. And for what it's worth, there is a premium for people that can communicate very technical thing to non-technical people, so if you've got any experiences like that it would be super helpful.
Best of luck on the job search!
Best of luck on the job search!