Create a resume for the Analytics domain – Day 8

Create a resume for the Analytics domain

In today’s data-driven world, the demand for skilled professionals in the analytics domain is on the rise. Whether you are an experienced data analyst or someone looking to break into the field, having a compelling resume is essential to make a strong impression on potential employers. A well-crafted resume can highlight your skills, experiences, and achievements, showcasing your potential as an asset to any organization. To help you create a winning resume for the analytics domain, here are some essential tips and guidelines to follow:

  1. Tailor Your Resume: Customize your resume according to the specific job description and requirements of the position you are applying for. Highlight your relevant skills and experiences that match the needs of the role. This tailored approach demonstrates your understanding of the job and how you can add value to the organization.
  2. Clear and Concise Format: Use a clean and professional format that is easy to read. Organize your resume into distinct sections such as a professional summary, skills, work experience, education, and certifications. Use bullet points to emphasize key points and make it easier for recruiters to scan through your resume quickly.
  3. Professional Summary/Objective: Start your resume with a strong professional summary or objective statement that highlights your experience, expertise, and career goals in the analytics field. Make it concise and compelling to grab the attention of the hiring manager.
  4. Highlight Your Analytical Skills: Showcase your proficiency in data analysis, statistical modeling, data visualization, and any relevant software tools such as Python, R, SQL, Tableau, or other analytics platforms. Provide specific examples of how you have used these skills to solve complex problems or make data-driven decisions in your previous roles.
  5. Quantify Your Achievements: Quantify your achievements and contributions wherever possible. Use specific metrics, percentages, or numbers to demonstrate the impact of your work. For instance, highlight how you improved operational efficiency, optimized marketing campaigns, or enhanced business performance through your analytical insights.
  6. Showcase Relevant Experience: Emphasize your experience in handling and interpreting large datasets, conducting market research, performing trend analysis, and generating actionable insights. If you have prior experience in handling specific projects or implementing data-driven strategies, provide detailed descriptions of your role and accomplishments.
  7. Education and Certifications: List your academic qualifications, relevant coursework, and any certifications related to analytics or data science. Include any specialized training or workshops you have attended to enhance your skills in the analytics domain.
  8. Keywords and Buzzwords: Incorporate relevant keywords and industry-specific buzzwords in your resume to ensure that it gets past applicant tracking systems (ATS) and reaches the hands of the hiring manager. Use terms that are commonly used in the analytics field to demonstrate your familiarity with industry-specific terminology.
  9. Attention to Detail: Ensure your resume is free from any grammatical errors or typos. Pay attention to formatting consistency and overall visual appeal. Use a professional font and maintain a consistent style throughout the document.
  10. Include a Cover Letter: Consider including a personalized cover letter that further highlights your interest in the position and your qualifications. Use the cover letter to explain why you are passionate about analytics and how your skills align with the company’s goals and values.

Create a resume for the Analytics domain

Create a resume for the Analytics domain

What is the difference between a Resume and a CV?

The terms “resume” and “CV” are often used interchangeably, but they refer to two distinct types of documents, particularly in the context of job applications. The main differences between a resume and a CV lie in their length, purpose, and the types of information included. Here’s a breakdown of the key distinctions:

  1. Length:
    • Resume: A resume is typically a concise document, usually not more than one or two pages, that highlights an individual’s relevant skills, work experience, and accomplishments. It is tailored to specific job positions and is meant to provide a quick overview of an applicant’s qualifications.
    • CV (Curriculum Vitae): A CV is more detailed and can be several pages long, especially for individuals with extensive academic or research backgrounds. It includes a comprehensive list of an individual’s educational and academic achievements, research experience, publications, presentations, and professional associations.
  2. Purpose:
    • Resume: Resumes are commonly used in the United States and Canada for most job applications, especially in the corporate sector. They focus on the applicant’s work experience, skills, and achievements relevant to the job being applied for.
    • CV: CVs are typically used in academic, research, and medical fields, or when applying for positions in Europe, the Middle East, Africa, or Asia. They are more comprehensive and detail-oriented, providing an exhaustive overview of an individual’s academic and professional background.
  3. Content:
    • Resume: A resume emphasizes work experience, skills, achievements, and relevant qualifications related to the job. It may include a summary or objective statement at the beginning and is often tailored to the specific job description or industry.
    • CV: A CV includes detailed information about an individual’s academic background, research experience, publications, presentations, academic awards, affiliations, and other relevant academic or professional accomplishments. It is comprehensive and provides a complete overview of one’s professional journey.
  4. Usage:
    • Resume: Resumes are the preferred document for most job applications in the corporate and business sectors.
    • CV: CVs are generally used in academic and research-oriented fields, such as academia, medicine, or scientific research.

Understanding the differences between a resume and a CV is crucial when applying for jobs in different regions and industries. It’s important to tailor your application materials accordingly to meet the expectations of the hiring practices in the specific field or location you are applying to.

Well, a resume looks good only when your interviewer can get a picture of your complete corporate or college journey.

How to create your resume in a better way?


Just an FYI – We do have a complete resume makeover service that involves a 30 minutes one-on-one call with you to understand the transformation that you need to do. Then we prepare the complete ATS enabled resume and make changes to your projects to make it more suitable and relevant for the recruiter. We again get it reviewed by you and then you can use this resume for application.

1000+ users have already used this service and we have received a very overwhelming response for our service. In case you have any query or want to avail this service then do drop an email on nitinkamal132@gmail.com and we will take it froward from there.

Email id for further information – nitinkamal132@gmail.com


Here are a few pointers for your resume:-

– Start with the introduction but keep it like a one-liner. You can also skip it (wink), no one cares if you are an enthusiastic data analyst 

– Keep your academic after that, preferably in the college -> 12th -> 10th order. Also, if you have good grades, then write it there else skip and mention only the year of passing out. (No one will know if you got 60% or 95%)

– Now comes the work experience. This is important, first, write about the company experience and then move to the project experience. Ex. I have worked in 3 companies in the past 8 years. My resume will look like:

1. Mu Sigma (2015 – 2018)

– Worked for multiple Fortune 500 clients in the domain of Telecommunication, Search Engine, e-commerce

– Led a team of 5 members where the key responsibility was to gather requirements, work on deriving logic for metrics and present them to higher management in WBR and MBR

– conducted learning hours on Python (that’s a lie, but who knows :P)

2. OYO

3. Ola (2021-Currenltly)

In the work ex part try to avoid mentioning the project description and try to showcase your leadership qualities(even if you have not led even yourself in a project :P)

– Now define a few projects.

Thumb rule – Your number of projects should not be more than the following:-

a. 0 to 3 years experience – 2 to 3 projects

b. 3 to 5 years – 3 to 4 projects

c. 5 to 8 years – 4 to 5 projects. At this point, your work experience part should increase and the project will slowly decrease

How to define a project?

STAR – 

Situation – The client or company was facing a churn rate of 30% on their e-commerce page

Task – The challenge was to identify the issues faced by the customers before dropping off and bring the churn rate to 10%

Action – Performed EDA to identify the fall-outs on every page, then derived metrics like lack of intent, lack of clarity, etc. to find out the reason for churn

Result – Deployed the model or presented the outcome to the CXOs group and created an A/B testing environment to deploy the changes. In 3 months the churn decreased to 17%.
Or you can write like – Saved 30 man hours per month by automation

Or save 300k dollars (DO NOT bloat the number by writing saved 33 Billion dollars and 645 Kgs of gold)

Then write

Tools and technologies used – SQL, Python, wagerah wagerah (All lies)

Certificates:-

– If you have a few certificates then it is good to go, but if not then try to get the free certificates like the one that is from Hacker Rank (SQL), some easy to get Udemy or Coursera certificate.

There is not a lot of advantage of getting all these certificates but its like something is better than nothing

Extracurricular – 

– Good to avoid, fill it only if you have less than 3 years of experience or if you are GOAT in any sports like rubik’s cube or cricket or anything

Let it be plain and simple.

Where to apply?

For analytics role we suggest the following websites:

– iimjobs.com (even if you are not from iims)
– hirect
– hirist
– Naukri (take the premium membership)
– Fishbowl (for referrals)
– Analytics opportunities page on facebook
– Monster jobs 
– Indeed

If you want to make a quick switch then apply to all the jobs. Ex. if my CTC is 12 LPA then I will apply for jobs paying 10 to 25 LPA. Lower CTC jobs will help you to practice for better companies.

But, also try to read as many topics as possible to put it in your resume and also to learn new technologies. 

Where can you fail?

By covering less topics for interviews

By trying to be a master of one technology 

By learning a lot but unable to answer interview questions. In every college there are people who are good in grasping concepts but are unable to score in the exams. In college, it was cool, but not in interviews. You need to know what questions are asked and up to what level you need to master a topic. There are multiple websites and youtube channels that tries to teach concepts. But, we at The Data Monk believe in Return on Investment. If I have read something, I should be able to answer basic to moderate level questions and should be able to put it on my resume

Our services

  1. YouTube channel covering all the interview-related important topics in SQL, Python, MS Excel, Machine Learning Algorithm, Statistics, and Direct Interview QuestionsLink – The Data Monk Youtube Channel
  2. Website – ~2000 completed solved Interview questions in SQL, Python, ML, and Case StudyLink – The Data Monk website
  3. E-book shop – We have 70+ e-books available on our website and 3 bundles covering 2000+ solved interview questionsLink – The Data E-shop Page
  4. Instagram Page – It covers only Most asked Questions and concepts (100+ posts)Link – The Data Monk Instagram page
  5. Mock InterviewsBook a slot on Top Mate
  6. Career Guidance/MentorshipBook a slot on Top Mate
  7. Resume-making and reviewBook a slot on Top Mate 

The Data Monk e-books

We know that each domain requires a different type of preparation, so we have divided our books in the same way:✅ Data Analyst and Product Analyst -> 1100+ Most Asked Interview Questions

Business Analyst -> 1250+ Most Asked Interview QuestionsData Scientist and Machine Learning Engineer -> 23 e-books covering all the ML Algorithms Interview Questions Full Stack Analytics Professional2200 Most Asked Interview Questions

The Data Monk – 30 Days Mentorship program

We are a group of 30+ people with ~8 years of Analytics experience in product-based companies. We take interviews on a daily basis for our organization and we very well know what is asked in the interviews.Other skill enhancer websites charge 2lakh+ GST for courses ranging from 10 to 15 months.

We only focus on making you a clear interview with ease. We have released our Become a Full Stack Analytics Professional for anyone in 2nd year of graduation to 8-10 YOE. This book contains 23 topics and each topic is divided into 50/100/200/250 questions and answers. Pick the book and read it thrice, learn it, and appear in the interview.

We also have a complete Analytics interview package
2200 questions ebook (Rs.1999) + 23 ebook bundle for Data Science and Analyst role (Rs.1999)
4 one-hour mock interviews, every Saturday (top mate – Rs.1000 per interview)
4 career guidance sessions, 30 mins each on every Sunday (top mate – Rs.500 per session)
Resume review and improvement (Top mate – Rs.500 per review)

Total cost – Rs.10500
Discounted price – Rs. 9000


How to avail of this offer?
Send a mail to nitinkamal132@gmail.com

Our services

  1. YouTube channel covering all the interview-related important topics in SQL, Python, MS Excel, Machine Learning Algorithm, Statistics, and Direct Interview Questions
    Link – The Data Monk Youtube Channel
  2. Website – ~2000 completed solved Interview questions in SQL, Python, ML, and Case Study
    Link – The Data Monk website
  3. E-book shop – We have 70+ e-books available on our website and 3 bundles covering 2000+ solved interview questions
    Link – The Data E-shop Page
  4. Instagram Page – It covers only Most asked Questions and concepts (100+ posts)
    Link – The Data Monk Instagram page
  5. Mock Interviews
    Book a slot on Top Mate
  6. Career Guidance/Mentorship
    Book a slot on Top Mate
  7. Resume-making and review
    Book a slot on Top Mate 

The Data Monk e-books

We know that each domain requires a different type of preparation, so we have divided our books in the same way:

Data Analyst and Product Analyst -> 1100+ Most Asked Interview Questions

Business Analyst -> 1250+ Most Asked Interview Questions

Data Scientist and Machine Learning Engineer -> 23 e-books covering all the ML Algorithms Interview Questions

Full Stack Analytics Professional2200 Most Asked Interview Questions

The Data Monk – 30 Days Mentorship program

We are a group of 30+ people with ~8 years of Analytics experience in product-based companies. We take interviews on a daily basis for our organization and we very well know what is asked in the interviews.
Other skill enhancer websites charge 2lakh+ GST for courses ranging from 10 to 15 months.

We only focus on making you a clear interview with ease. We have released our Become a Full Stack Analytics Professional for anyone in 2nd year of graduation to 8-10 YOE. This book contains 23 topics and each topic is divided into 50/100/200/250 questions and answers. Pick the book and read it thrice, learn it, and appear in the interview.

We also have a complete Analytics interview package
2200 questions ebook (Rs.1999) + 23 ebook bundle for Data Science and Analyst role (Rs.1999)
4 one-hour mock interviews, every Saturday (top mate – Rs.1000 per interview)
4 career guidance sessions, 30 mins each on every Sunday (top mate – Rs.500 per session)
Resume review and improvement (Top mate – Rs.500 per review)

Total cost – Rs.10500
Discounted price – Rs. 9000


How to avail of this offer?
Send a mail to nitinkamal132@gmail.com

Author: TheDataMonk

I am the Co-Founder of The Data Monk. I have a total of 6+ years of analytics experience 3+ years at Mu Sigma 2 years at OYO 1 year and counting at The Data Monk I am an active trader and a logically sarcastic idiot :)