Resume Building

Name
Data Analyst
Your City, ST 12345
123.456.7890
 ㅡ

Skills | * Strong analytical skills
* Pattern recognition
* Relational databases and SQL
* Strong data visualization skills
 ㅡ
Experience | Company Name / Job Title
MONTH 20XX - PRESENT,  LOCATION
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean ac interdum nisi. Sed in consequat mi. Sed in consequat mi, sed pulvinar lacinia felis eu finibus.

Company Name / Job Title
MONTH 20XX - MONTH 20XX,  LOCATION
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean ac interdum nisi. Sed in consequat mi.

Company Name / Job Title
MONTH 20XX - MONTH 20XX,  LOCATION
 ㅡ
Education | School Name / Degree
MONTH 20XX - MONTH 20XX,  LOCATION
Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore.

School Name / Degree
MONTH 20XX - MONTH 20XX,  LOCATION
 ㅡ
Awards | Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean ac interdum nisi. Sed in consequat mi. Sed pulvinar lacinia felis eu finibus.

Kaggle's Careercon https://www.youtube.com/playlist?list=PLqFaTIg4myu-npFrYu6cO7h7AI6bkcOlL

Building a Portfolio https://www.youtube.com/watch?v=xrhPjE7wHas&list=PLqFaTIg4myu-dNobDHQZPrD2wH27PthCG

Interview Process https://www.youtube.com/watch?v=X6orAXDIrds&list=PLqFaTIg4myu-dNobDHQZPrD2wH27PthCG&index=6

Common Interview Questions https://www.youtube.com/watch?v=aXUsrKPTBvY&list=PLqFaTIg4myu-dNobDHQZPrD2wH27PthCG&index=7

Am I a good fit? https://www.youtube.com/watch?v=0W0Zrc-m5r8&list=PLqFaTIg4myu-dNobDHQZPrD2wH27PthCG&index=3

Career Switching https://www.youtube.com/watch?v=iP0Fxg4oqUQ&list=PLqFaTIg4myu-dNobDHQZPrD2wH27PthCG&index=9

### Professional Skills

1. Structured Query Language (SQL): SQL is considered a basic skill that is pivotal to any entry-level data analyst position. SQL helps you communicate with databases, and more specifically, it is designed to help you retrieve information from databases. Every month, thousands of data analyst jobs posted require SQL, and knowing how to use SQL remains one of the most common job functions of a data analyst.

2. Spreadsheets: Although SQL is popular, 62% of companies still prefer to use spreadsheets for their data insights. When getting your first job as a data analyst, the first version of your database might be in spreadsheet form, which is still a powerful tool for reporting or even presenting data sets. So, it is important for you to be familiar with using spreadsheets for your data insights.

3. Data visualization tools: Data visualization tools help to simplify complex data and enable the data to be visually understood. After gathering and analyzing data, data analysts are tasked with presenting their findings and making that information simple to grasp. Common tools that are used in data analysis include Tableau, Microstrategy, Data Studio, Looker, Datarama, Microsoft Power BI, and many more. Among these, Tableau is best known for its ease of use, so it is a must-have for beginner data analysts. Also, studies show that data analysis jobs requiring Tableau are expected to grow about 34.9% over the next decade.

4. R or Python programming: Since only less than a third of entry-level data analyst positions require knowledge of Python or R, you don’t need to be proficient in programming languages as an entry-level data analyst. But, R or Python are great additions to have as you become more advanced in your career.

### Soft Skills

1. Presentation skills

Although gathering and analyzing data is a big part of the job, presenting your findings in a clear and simple way is just as important. You will want to structure your findings in a way that allows your audience to know exactly what conclusions they are supposed to draw.

2. Collaboration

As a data analyst, you will be asked to work with lots of teams and stakeholders—sometimes internal or external—and your ability to share ideas, insights, and criticisms will be crucial. It is important that you and your team—which might consist of engineers and researchers—do your best to get the job done.

3. Communication

Data analysts must communicate effectively to obtain the data that they need. It is also important that you are able to work and clearly communicate with teams and business leaders in a language that they understand.

4. Research

As a data analyst, even if you have all of the data at your disposal, you still need to analyze it and draw crucial insights from it. To analyze the data and draw conclusions, you will need to conduct research to stay in-line with industry trends.

5. Problem-solving skills

Problem-solving is a big part of a data analyst’s job, and you will encounter times when there are errors in databases, code, or even the capturing of data. You will have to adapt and think outside the box to find alternative solutions to these problems.

6. Adaptability

In the ever-changing world of data, you have to be adaptable and flexible. As a data analyst, you will be working across multiple teams with different levels of needs and knowledge, which requires you to adjust to different teams, knowledge levels, and stakeholders.

7. Attention to detail

A single line of incorrect code can throw everything off, so paying attention to detail is critical for a data analyst. When it comes to understanding and reporting findings, it helps if you focus on the details that matter to your audience.

### Adding soft skills to your resume

Here are a few ways that you can add soft skills to your resume:

1. Analyze your previous work experience and find opportunities to insert a soft skill. For example, if you worked in a restaurant, you could emphasize your communication and adaptability skills that you utilized to effectively function during peak hours.
2. Call attention to your problem-solving, presentation, research, and communication skills in previous projects or relevant coursework.
3. Add a mix of soft and professional skills in the skills or summary section of your resume.

Question 1

## Activity overview

In the last activity, you added skills to your resume. In this activity, you will work on your resume by adding your experience.

By the time you complete this activity, you will understand how to frame your work history and experience to fit your resume. This will enable you to build a document that effectively describes your skills, experience, and achievements. This is important for applying for jobs as a data analyst.

### What you will need

To get started, open up the resume template that you chose in the previous activity. If you can’t find the template you chose, you can access the resume templates below.

First, access the templates (if needed) as well as the Work Experience Bullet Example.

To use the templates for this course item, click the links below and select “Use Template.”

Link to resume template 1: Resume Template 1

Link to resume template 2: Resume Template 2

Link to example document: Work Experience Bullet Example

OR

If you don’t have a Google account, you can download the templates directly from the attachments below.

## Best practices for writing about experience

One of the most important functions of a resume is communicating your prior work experience in a favorable light. This can often be challenging, as the one-page format forces job seekers to summarize all of their work experience into a few bullet points.

Resume best practices will help you select the most relevant parts of your work experience and communicate them in the shortest, most impactful way possible.

As you think about how to represent your work experience on your resume effectively, it might be helpful to refer to these best practices:

Focus on your accomplishments first, and explain them using the formula “Accomplished X, as measured by Y, by doing Z.”

* These statements help you communicate the most important things a recruiter or hiring manager is searching for—the impact of your work.
* Whenever possible, use numbers to explain your accomplishments. For example, “Increased manufacturing productivity by 15% by improving shop floor employee engagement,” is better than “Increased manufacturing productivity.”

Phrase your work experience and duties using Problem-Action-Result (PAR) statements.

* For example, instead of saying “was responsible for two blogs a month,” phrase it as “earned little-known website over 2,000 new clicks through strategic blogging.”

Describe jobs that highlight transferable skills (those skills that can transfer from one job or industry to another).

* This is especially important if you are transitioning from another industry into data analytics.
* For example, communication is a skill often used in job descriptions for data analysts, so highlight examples from your work experience that demonstrate your ability to communicate effectively.

Describe jobs that highlight your soft skills.

* These are non-technical traits and behaviors that relate to how you work.
* Are you detail-oriented? Do you have grit and perseverance? Are you a strong critical thinker? Do you have leadership skills?
* For instance, you could give an example of when you demonstrated leadership on the job.
* Showing is always more effective than telling.

This is almost always the hardest part of crafting a resume, especially if you are transitioning from a different career field. However, if you take a moment to think deeply about your previous work experience, you’ll likely discover that you can find ways to represent your work experiences in a way that highlights your ability to do things important to data analyst roles, such as thinking critically or making data-driven decisions.

### Get the interview first

Remember that the goal of a resume is to get you an interview. You may find that you need to brainstorm and carefully edit your resume to effectively summarize your background. In the end, you will have all of your various responsibilities and accomplishments from previous jobs synthesized into a few bullet points. That way, your resume will highlight what potential employers like to know about applicants.

Effective resumes communicate that you are a candidate who understands the needs of the role and you have the skills and experience to warrant an interview. During interviews, you can expect questions about your experience and that’s when you can go into more detail.

## Add your work experience

Now that you have had some time to think about your work experience, add it to your resume. Keep in mind the best practices we shared above and that creating a resume is a process. You’ll likely come back to work on it multiple times and change phrasing or formatting. With effort and time, you’ll eventually get your resume to a place where you’re satisfied with the final result.

### Sample experience description

Earlier, you downloaded a template of bullet points describing work experience. Refer to this as you write about your own work experience. Notice how it demonstrates factual, measurable successes and job experience that is applicable to the role of a data analyst in a short, concise manner.

If you need inspiration or want to see how other data analysts have structured their resumes, take a moment to search for resumes of real data analysts. You can find these easily on sites such as LinkedIn. Seeing how other data analysts have structured and worded their own resumes may give you valuable insight about more effective ways to highlight your own experience.