How should a junior data scientist resume be structured when experience is limited?

Put education and relevant training first, then emphasize skills, certifications, internships, and projects tailored to the role. Use action bullets that explain methods, tools, and outcomes to demonstrate technical readiness.

Wishing to kick start your career as a junior data scientist?

One of the most crucial tools that will help you realize your dream to land a job as a data scientist is having a data scientist resume that showcases your skills and knowledge.

Even if you don’t have significant experience as a professional, you can still make an impressive data scientist resume as a fresher by emphasizing your skills, certifications, internship experience, and projects.

Plus, with the booming demand and job opportunities for data scientists which are projected to grow by 36% by 2031, now is a good time to build a stellar resume and send out those applications.

In this blog, we will show you what a perfect entry-level data scientist resume looks like, along with pointers on why it works well so that you can use it as a reference to build your own.

Entry-level Data Scientist Resume Example


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Tips & Guides
Chris Pine
Entry-level Data Scientist
SUMMARY
Data-driven computer science graduate with 10+ months of experience in developing analytic models to process raw data for identifying product improvement opportunities. Skilled in deploying machine learning modeling algorithms for recognizing customer sentiments to enhance customer satisfaction. Proficient in executing data mining and analysis techniques like clustering, association, and classification.
KEY SKILLS
• Data Analysis • Data Mining • Project Delivery • Predictive Modelling & Analytics • Machine Learning
• Software Programming • Process Improvement
TECHNICAL SKILLS
• Languages: Python, R, Spark, SQL, Java
• Tools, Models & Frameworks: Tableau, Scikit-learn, TensorFlow, NLP, NoSQL
EDUCATION
Data Science Fundamentals & Advanced Bootcamp
Coursera
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    • Course Modules:
    • Data Science Life Cycle |Common terminologies of Data Science| Basics of databases using SQL | Machine Learning
    • Problem Formulation and Framework | Hypothesis Building and Framework | Excel Basics, Formulas and Functions
    Bachelor of Technology in Computer Science & Engineering
    University of Massachusetts
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      • GPA: 4.5
      PROFESSIONAL EXPERIENCE
      Junior Data Analyst
      Plaxonic Technologies
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        • Collecting and analyzing data using Tableau to identify user's purchase patterns for supporting business decisions
        • Maintaining report dashboards to reduce data processing time and monitor key performance indicators
        • Migrating server data from legacy system to a unified database to unify disparate data and reduce costs by 20%
        • Analyzing survey data for ensuring data integrity to increase business efficiency, mitigate risks, and increase revenue
        INTERNSHIP
        Data Analyst (Intern)
        Google
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          • Assisted the technical team of 10+ professionals to develop advanced analytics models for improving products & services
          • Collaborated with senior data scientists to deploy machine learning models to evaluate POS tagging using data mining
          • Researched and mined data to support database for streamlining the data visualization process
          • Coordinated with 5 junior data scientists to plan and develop presentations for senior executives & external stakeholders
          PROJECTS
          • GitHub Swagger UI Analysis | GitHub | Nov '21
          • Predicted the programming language of a repository with 71% accuracy via NLP given the context of the Swagger UI file
          • Employed an API to bring in the Swagger UI files and programming language of each repository
          • Utilized techniques such as lemmatizing, tokenizing, removing non-ASCII characters, and dropping outliers
          • Data Sentiment Analysis for Infosys | GitHub | Mar '21
          • Estimated the ROI of the online marketing efforts of Infosys to help boost sales and increase revenue
          • Utilized Natural Language Processing (NLP) to extract positive, negative, and neutral sentiments from textual data
          • Executed sentiment analysis on textual data to monitor brand and product sentiment for understanding customer needs

          Use the template NOW!

          This template for an aspiring data scientist fresher highlights the educational qualifications, skills, certifications, and projects to help the candidate stand out to recruiters.

          The education section is placed at the top part of the resume and the courses modules for the data scientist boot camp have been included to show the relevance of the candidate’s knowledge for the role.

          Additionally, the candidate’s experience as a junior data analyst has been described in a way that showcases the technical skills and knowledge that is necessary for the role of a data scientist.

          And instead of simply listing the personal projects that the candidate has worked on, including specific pointers on how the candidate executed the project provides more clarity around the candidate’s skills and experience.

          Minor factors like these help make a stellar data scientist resume even with no significant experience in the field.

          If you want to create a similar resume for yourself, use Hiration’s AI-powered resume builder with 24x7 chat support. You can also write to us at support@hiration.com to resolve any queries.

          Also Read: How to apply for data science jobs in 2023?

          Frequently Asked Questions

          • What should a junior data scientist resume include?

            Emphasize skills, certifications, internship experience, and projects. Place education at the top and include course modules to show relevance.

          • How do you write a junior data scientist resume with no professional experience?

            Focus on skills, certifications, internship experience, and projects. Minor factors help make a stellar resume even with no significant experience.

          • What should you put in a junior data scientist resume summary?

            Summarize a data-driven profile with 10+ months of experience, machine learning modeling algorithms, and data mining techniques like clustering, association, and classification.

          • Which technical skills should you list on a junior data scientist resume?

            Include Languages: Python, R, Spark, SQL, Java, and Tools, Models & Frameworks: Tableau, Scikit-learn, TensorFlow, NLP, NoSQL.

          • How should you order education on a junior data scientist resume?

            Place your education at the top and add course modules to show relevance for the role.

          • How should you present projects on a junior data scientist resume?

            Avoid simply listing projects. Include specific pointers on how you executed each project to clarify your skills and experience.

          • What internship or analyst experience helps your data scientist resume?

            Describe junior data analyst experience to showcase the technical skills and knowledge necessary for a data scientist role.

          • Is demand for data scientists growing?

            Yes. Demand and job opportunities for data scientists are projected to grow by 36% by 2031, so now is a good time to build a resume and send out those applications.

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