Top Data Science Intern sections that make the best resume
- Header
- Professional summary
- Experience (with numbers and results)
- Relevant skills
- Education
- Certifications
How to write a Data Science Intern resume experience section
Data Science Intern Resume’s Job Experience Checklist:
- Use 4-6 bullet points per job title;
- Don’t go further than a decade behind when describing your job history, unless you’re applying for an executive position;
- Combine job responsibilities as well as achievements with numbers in results when you describe your past work;
- Start each sentence with a power verb and avoid overused buzzwords;
- Use either C-A-R or S-T-A-R methodology, when describing your experience.
The work experience samples below come from real Data Science Intern resumes that got people hired at top companies. You can use them as an inspiration to build your own resume:
- Analyzed massive social networks (350+ million vertices) using a variety of tools (Hive, Pig, Python).
- Used findings of academic paper [Gleich and Seshadhri, 2012] to develop scalable application for community detection algorithm in Apache Pig. Application is now used by a variety of internal clients (Big Data CoE, Mobility).
- Collaborated with various business units to create community and node level features describing customer behavior from the AT&T social network. Features have been used in churn modeling and customer intervention.
- Created a Model Which predicts the Redemption of Mutual Fund by an Investor in future.
- Cross sell analytics of Capital Market products.
- Technology Used: R ,Machine Learning and TIBCO Spotfire for Data Visualization
- Developed the recommendation algorithm for the Makeup Genius mobile application based on user demographics & interactions within the application, using Hadoop and Java
- Utilized secondary sorting through partitioners, composite key comparators, and key grouping comparators in Hadoop to reduce the runtime of the algorithm by 70%
- Designed a standard format for post-processed data to be used in algorithms & visualizations
- Created geo-location & timeline based visualizations for L’Oreal Paris product data regarding which products received the most interest along those parameters through Python (Pandas, Matplotlib)
- Implemented Machine Learning (XGBoost) on sample data sets to analyze the relationship between demographic variables and purchasing behavior with Python
- Data mining of Yougov Profiles survey data utilizing predictive modeling and time series analysis to provide market research forecasting for Advertising Sales clients
- Execute advanced analytics / machine learning techniques (regression, ANOVA, k-means clustering, decision tree classifier models) on data sets pertaining to Viacom's digital content viewership
- Develop statistical models predicting success metrics for online digital video posts on social media sites
- Compose and present decks containing high-level media and consumer research findings for Ad Sales research partners
- Use of data science tools including Python, R, and more
- Exposure to media data sources including: MRI, Yougov, Kantar, Nielsen National TV Toolbox, ComScore, Youtube Analytics, Anametrix, Nielsen Buyer Insights, and Nielsen Catalina Solutions
- Worked on a sensor data summarization project that required knowledge and applications of signal processing and advanced statistical techniques.
- Extensive experience with R.
- Got introduced to SQL, UNIX shell and Git.
- Contributed to the code repository.
- Use Python and R to collect and clean data from 5 external sources.
- The data set contains information of 14000 rentals in Greater Boston Area; 15 features of houses are used as predictors.
- Visualize data using Tableau and R.
- Develop machine learning pricing models for rental market in Greater Boston Area.
- Compose a report using R each week; present findings using Microsoft PowerPoint to CEO and CTO every week.
- Analyzed massive social networks (350+ million vertices) using a variety of tools (Hive, Pig, Python).
- Used findings of academic paper [Gleich and Seshadhri, 2012] to develop scalable application for community detection algorithm in Apache Pig. Application is now used by a variety of internal clients (Big Data CoE, Mobility).
- Collaborated with various business units to create community and node level features describing customer behavior from the AT&T social network. Features have been used in churn modeling and customer intervention.
- Graduate internship in the Wholesale Banking Advanced Analytics team
- Master's project on a recommender system for financial markets products
- Thesis topic: Uncertainty Analysis of Predictions by Recommender Systems based on Matrix Factorization Models
- Analyzed massive social networks (350+ million vertices) using a variety of tools (Hive, Pig, Python).
- Used findings of academic paper [Gleich and Seshadhri, 2012] to develop scalable application for community detection algorithm in Apache Pig. Application is now used by a variety of internal clients (Big Data CoE, Mobility).
- Collaborated with various business units to create community and node level features describing customer behavior from the AT&T social network. Features have been used in churn modeling and customer intervention.
- Use Python and R to collect and clean data from 5 external sources.
- The data set contains information of 14000 rentals in Greater Boston Area; 15 features of houses are used as predictors.
- Visualize data using Tableau and R.
- Develop machine learning pricing models for rental market in Greater Boston Area.
- Compose a report using R each week; present findings using Microsoft PowerPoint to CEO and CTO every week.
- Assist data science team in development of analytical models for product lines.
- Assist in building of innovative data products using cutting edge technologies and Business Intelligence tools such as Tableau in a fast paced environment.
- Responsible for the development and preparation of a broad range of dashboards for management.(reporting)
- Develop ad-hoc queries and provide analytical support and recommendation as necessary.
- Working with data mining methods, reliability analysis, simulation, and optimization.
- Work with scrap data from the web open API's or data of interest to the team.
- Gather and analyze business requirements from non-technical users and translate into detailed functional requirements that meet business needs.
- Diagnosed and intercepted website errors of the leading national airline "Pobeda"
- Extracted data (2500 customer reviews). Converted it into a readable form and recorded it in a text file
- Provided frequency and empirical data analysis using Python (pymorphy2, re, numpy, matplotlib)
- Involved in data management processes: data mining, data processing, data structuring, data visualisation.
- Utilised Microsoft SQL Server Management Studio, Microsoft Power BI and Microsoft Azure Machine Learning Studio.
- Implemented machine learning techniques and algorithms to model and predict data.
- Improve document classification result by extracting key sentences and trained sentence embedding using Universal Sentence Encoder
- Cleaned text documents through text processing
- Modularized the model training pipeline to allow for flexible changes
- Discovered domain-specific terms by studying word informations using a decision tree classifier, expanded the dictionary by 30%
- Used Keras to preprocess data for the construction of CRF and biLSTM model for discovery of domain-specific terms
- Developed a knowledge graph for industry categories using word2vec, K-means Clustering, led to more accurate recommendations for clients
- Used linguistic rules and regex to detect vague expressions in CVs
PRO TIP
Include quantitative data throughout your Data Science Intern resume to impress the hiring manager. Real facts and figures that show off your competency as an audit manager go a long way. Did you reduce the costs of audits? Manage a large team? Boosted efficiency? Show off the real numbers!
Action Verbs for your Data Science Intern Resume
Recommended reads:
Data Science Intern Resume Skills’ Tips & Tricks to Impress Recruiters
Resume Skills Section Checklist:
- Ensure your hard skills section (including technologies) are exactly matching the job description.
- Don’t simply list your soft skills. Apply the “show, don’t tell” principle - let your job achievements speak for themselves.
- Find a way to showcase your skills beyond the skills section.
- Your resume’s skill section is important to ATS systems - so don’t skip it.
Top Skills for your Data Science Intern resume
- Rstudio
- Jupyter
- Mahout
- Scikit
- Graphlab
- Gephi
- Communication
- Adaptability
- Commitment
- Self-learning
- Curiosity
- Persistence
PRO TIP
When picking skills to feature in your resume, make sure they'll be relevant to the position you’re applying to. The point of listing skills is for you to stand out from the competition. Stay away from repetitive, meaningless skills that everyone uses in their resumes. Or else, they’ll backfire and make you look like an average candidate.
Data Science Intern Resume Header: Tips, Red Flags, and Best Practices
CHECKLIST For Your Data Science Intern Resume Header
- Your name and surname in a legible and larger resume font
- The job title you’re applying for or your current job title as a subheading to your name
- Link to your portfolio or online profile, such as LinkedIn
- Address (City and State for the US; just your city for rest of the world)
- Email address
- Headshot (required or welcomed in the EU; not required and sometimes frowned upon in the US)
Stick to popular email providers such as Gmail or Outlook. And use these professional formats to create your username:
- first.last@gmail.com
- last.first@gmail.com
- firstlast@gmail.com
- f.last@gmail.com
- first.l@gmail.com
Recommended reads:
PRO TIP
Some companies, states, and countries have non-discrimination policies about what kind of information can be included on your Data Science Intern resume. This might include a photo (which is often included in a resume header and might be on personal web pages you link to). You can always email the company’s HR department to ask about their policies before you apply.
Data Science Intern Resume Summary Best Practices
Checklist: What to include in your Data Science Intern resume summary:
- Years of experience;
- Highlight top 3 skills and proficiencies;
- One big professional accomplishment you’re most proud of, that you can tie with the aforementioned skills;
- Use short, direct sentences - but no more than three - to keep the HRs interested.
Resume Summary Formula:
PRO TIP
Your summary section should act as a professional taster. Use it wisely. Effectively convey your professional profile and let the hiring manager know that if they hire you, they won’t be disappointed. Make sure to include keywords from the job description too! Elaborate on your abilities further in your experience section. Again, cater to the job description.
Recommended reads:
Listing Your Education, Certifications and Courses
Resume Education Section Checklist:
- Ensure your hard skills section (including technologies) are exactly matching the job description.
- Don’t simply list your soft skills. Apply the “show, don’t tell” principle - let your job achievements speak for themselves.
- Find a way to showcase your skills beyond the skills section.
- Your resume’s skill section is important to ATS systems - so don’t skip it.
Top Certifications for your Data Science Intern resume
Recommended reads:
PRO TIP
If you hold a certain major and a minor, your majors should be mentioned first.
Data Science Intern Resume: Additional Writing & Formatting Tips
There are three basic resume formats you can choose from:
- Reverse-chronological resume format;
- Functional resume format;
- Hybrid (or Combination) resume format;
The most optimal format for your particular case will depend on your years of experience, as well as whether you’re switching industries or not.
Reverse chronological resumes are best suited for experienced individuals who are sticking to their industry. The experience section takes a central place, and its bullets contain your responsibilities and achievements, coupled with numbers and results.
Functional resumes are used by less experienced jobseekers or career changers. Note that it’s not a format that recruiters prefer, as most are used to the classic chronological alignment. Instead of a list of job titles, functional resumes focus on your skills, and through what experiences you gained them.
Hybrid resumes are great for both experienced and entry-level candidates, as well as career changers. They combine the best of both worlds - most often in a double column format, where one side of the content is focused on your experience, whereas the other - on your skills, strengths, and proudest moments.
Data Science Intern Resume Summary best practices
Here are more resume tips regarding your layout and style:
- Clear and legible 12p resume font size;
- Use 10’’ resume margins - that’s default for a great resume design;
- Use a one-page template resume length if you’ve got less than 10 years of experience; otherwise, opt for a two-page resume;
- Save your resume as PDF before sending it to the recruiter.
To take it a step further, check out how your resume can stand out without leaning too much on the creative side.
Recommended reads:
PRO TIP
Test your draft Data Science Intern resume by sending it out to peers and mentors in your circles. Ask them to review it as if they are hiring you for a project and implement the feedback afterwards.
Other sections to include in your resume
Depending on the type of company (corporation or start-up; innovative or traditional), job seniority level and your location, you may want to include more sections to your Data Science Intern resume:
Data Science Intern Resume: How to Make Yours More Creative & Stand Out
When you send your resume to a potential employer, chances are it's the fiftieth one they've seen that day. That's why you need to make your Data Science Intern resume stand out for the right reasons. That means showing your personality, not just your professional experience. Employers are far more likely to remember a candidate who seems like a genuine person and not a robot. Do this by including your passions (which is also a great place to demonstrate skills on a resume), share your favorite books, or even what your usual day looks like.
What Makes a Great Data Science Intern Resume: Key Takeaways
- Choose a resume layout that sends the right message across and fits your current career situation;
- Create a resume header that shows your desired job title, and easy to find contact numbers;
- Be specific about your experience, accomplishments and future goals in your summary;
- Feature detailed metrics and specific examples that show the impact you made in your previous roles when describing your experience;
- List soft skills backed by examples;
- Add all of your technical skills and certifications that you have and match the job description;
- Show off a dash of personality in your resume that will demonstrate your culture fit and the right mix of hard and soft skills.
