Data Science Engineer Resume | Data Scientist Resume | Data Science Resume Tips | Intellipaat

01
What makes a
Good Resume?
04
02
Career in
Data Science?
03
05 06
Building a Data
Science Resume
Customizing and
Updating your Resume
Spell Check and
Proofreading
07
Data Science
Resume Samples
Do’s and Don’ts of a
Data Science Resume

What makes a Good Resume?

Copyright IntelliPaat, All rights reserved
What makes a good resume?
To make a good resume:
Pick the right format
and template
Proofread and Spellcheck to avoid
grammatical and spelling errors.
Keep it up-to-date and
relevant to the job

What makes a good resume?
To make a good resume:
List your educational
qualifications
Briefly describe previous
work experiences
Mention your skills
relevant to the job

Career in Data Science

What is Data Science?
The simplest answer: Making data of value and of use to us, and applying
it to the real world and practical scenarios is called data science. It is the
process of obtaining information and insight from data.
It is one of the most promising careers in today’s world!

Job Roles in Data Science
Data Analysts
They analyze large amounts of data, to decipher its
meaning and understand trends.
Skills – Mathematics, Statistics, Computer Science etc.
Business Intelligence Analysts
BI Analysts use data analysis to transform data
into insights that improve business value.
Skills – Statistics, SQL, C#, Python etc.

Job Roles in Data Science
Data Mining Engineers
They mine hidden information from large amounts of
data and suggest how this information can provide
value to the organization.
Skills – Java, PERL, Hadoop, Python, SQL etc.
Data Architects
They design secure electronic databases for
storing and organizing data, by understand the
organization’s existing data infrastructure.
Skills – ML, NLP, Applied Math, Statistics, etc.

Building a Data
Science Resume

Keeping it short
• List down everything that you want
to mention.
• The key is to make everything
concise and to-the-point.
• Choose the projects, certifications
that are most relevant to data
science.
• It is very important to prioritize.

Selecting a Resume Template
• Working on the visual appeal of the
resume makes it unique and your
resume stands out from the crowd.
• Pick a resume template according to
your own aesthetic preference.
• Pick a design template that is appealing
and unique, but yet simple and makes
the content easily readable.
• Using too many colors would do more
harm than good.

Profile and Contact Information
• Mention your email address, contact number and links to your LinkedIn and GitHub profiles.
• Make sure all your data science related projects are present on your GitHub account.
• Write a brief description about yourself, in 2-3 sentences that tells about your skills, interests and qualification.

Writing your skills
Skills should always be mentioned in order of relevance to the job role you’re applying for.

• Be it data mining or running
embedded systems, python
can do everything.
• The python library used for
data analysis is Pandas.
SQL Databases
Python Programming R Programming
• SQL is used to manage and
query data that is held in a
relational database system.
• It is used to read, retrieve,
update or insert data
• R Programming implements
ML algorithms to give us
many statistical techniques.
• It is used for calculations
and data manipulation.
Skills for a Data Science Resume

Data Visualization
Machine Learning
Business Strategy Artificial Intelligence
Skills for a Data Science Resume
• They should understand
business problems and
provide solutions.
• They use data in a way that
is helpful to the company.
• A data scientist should be
able to represent data
graphically.
• Visualization makes sense
of the large amount of data.
• ML analyzes data using
algorithms and automates a
data scientist’s jobs.
• Should be familiar with NLP
& Recommendation engines

Projects, Publications and Accomplishments
Since you’re seeking a role in the data science industry,
mentioning publications, projects and achievements
related to data science is very important.

Analytical and Communication Skills
• It is very important to justify your analytical and communication capabilities.
• Leadership and communication skills can be highlighted by mentioning projects
and experiences of working in a team setting, on collaborative projects.

Work Experience and Education
• Explain your role and responsibilities in each organization and the period of time you worked there for.
• After work experience, mention your educational background and names of institutions you studied in.

Selecting font style and arrangement
• Pick a font style and organize every
mentioned in a neat manner.
• It is best to mention projects,
accomplishments, employment
history and certifications in a reverse
chronological manner.

Proofreading and Spellcheck

Proofreading and Spellcheck
• It is always very important to check
for spelling and grammatical errors.
• Have someone go through your
resume to suggest changes or point
out any errors.

Customizing and
Updating your resume

Customizing and Updating
Always customize your resume for every job profile and company.

Data Science Resume Samples

Data Science Resume for a Fresher
For a fresher, building a strong
resume mentioning all your
skills is very important.
It is also crucial to make the
resume look unique and neat.

Data Science Resume for Experienced Professionals
For data science professionals with some experience in the field, mentioning
relevant work experience and responsibilities at each job role is crucial.

Do’s and Don’ts of a
Data Science Resume

Do’s and Don’ts
• Include updated contact information.
• For each work experience, include a brief summary about
your role and responsibility in the organization.
• While writing educational qualification, always mention
the name of the institute, and the time period you
studied there for.
• Include relevant project work.
• Make your resume look unique.
Don’ts
• Don’t include date of birth or religious beliefs.
• Don’t use vague descriptions for jobs and projects.
Mention exactly what you did, and what impact it had.
• Don’t list technologies and programming languages that
you’re not proficient in. Over exaggerated abilities will
get you rejected in the interview.
• Don’t make any grammatical errors.
• Don’t make your resume too generic. Customize it as per
job roles.
Do’s
Finally, now that you have learnt everything you need to know to build yourself the perfect data scientist resume, one
that makes your application stand out, let’s go over a few things you should do, and mistakes you should not make.

Final Thoughts

Final Thoughts
It is very important for everyone to make their resume stand out
from the crowd, in order to get a job in the data science industry.
Recruiters get thousands of applications and resumes, Don’t give
them any reasons to reject your application and remember to
pay attention to small details too.

Further Learning..

Further Learning

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Data Science Engineer Resume | Data Scientist Resume | Data Science Resume Tips | Intellipaat

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