I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (2024)

DISCLAIMER:This article is sponsored by SkillsFuture Singapore, the government agency leading the SkillsFuture movement. This writer tookdata courses[to switch careers to become aData Analyst] funded by SkillsFuture before committing to a more expensive course down the line.

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (1)

About a year ago, I packed up my belongings, returned the company key card, and said my farewells to colleagues. I had spent seven years as a journalist. Two in corporate communications. My next destination was something quite different – a data science bootcamp.

I had resigned from jobs before, but this was the first time I was quitting without another position already lined up.

Many would question the need for such a radical change. After all, why leave a stable career to pursue something that I had absolutely no experience in?

If I were to be absolutely honest, fear was a big factor.

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (2)

The career path in communications was seemingly more straightforward, but the relentless march of technology had unsettled me.

I had always thought as a writer, I’d not be affected. Even as all the talk about AI replacing jobs in Singaporewas ongoing, there were always comforting examples of machines epically failingat producing even passable writing.

Then I read about the rise of robot writersand Natural Language Processing, which has made vast improvements to Google Translateand Siri. Given how thoroughly the media industry has already been disrupted by technology, picking up digital skills suddenly sounded crucial.

One thing I’ve learnt is when change looks impossible, it will come drastically and abruptly when it eventually happens.

Case in point: For years, people had trouble getting a taxi at certain times and in certain areas of Singapore. Countless tweaks were made to the taxi system to no avail. Then ride-hailing apps stormed onto the scene and hailing a taxi became quaint overnight.

Like most salarymen, I was faced with two choices.

Option 1:Deepen and ride on my existing credentials for as long as possible and hope disruption doesn’t hit me, or

Option 2:bite the bullet and upskill.

If I were just a decade older and a tad closer to retirement, say,45 – Option 1 might have been a tempting choice.But I chose the latter as I was still only 34 and had my whole working life ahead of me.

So I chose a new career that built digital skills upon my existing analogue abilities.

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (3)

You might think I’m just jumping on the data science bandwagon as it’s the hottest thing and is a growing industry. That’s only half true.

While my career thus far (dealing mostly with words as a writer) may seem far removed from data analytics (with its cold hard numbers), there are actually numerous similarities:

A professional storyteller makes complex issues easily understandable. I saw data as an additional way to explain the world: Reporters are using machine learning in new forms of journalism while corporate communications professionals are vying to showcase their companies’ data abilities.

Data AnalystJournalist
Data analysts gather data through multiple sources such as tracking user behaviour and public databases.Journalists gather data through multiple sources such as expert interviews and public records.
Data analysts turn unstructured, unwieldy data that is often incomplete into easily understandable structured data that paint a whole picture.Communications professionals simplify lengthy, inscrutable corporate jargon into a sharp pitch that captures the essence of a subject.
Tell coherent stories with data.Tell coherent stories with information.

Being aware of these was immensely helpful at job interviews when faced with the question of “why should I hire someone with no experience?”

PS: If you’re curious what your career pathway could be, you can check out theSkills Frameworkfor some clarity. The one specifically for people in theICT sector here.

The key is to start small

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (4)

Many people imagine switching careers as taking an entire year off to complete a degree. This was partly true for me. Except that I used Skillsfuture Credit to take small ‘trials’ before I decided to take the leap.

These were the specific courses I took (the ones on Udemy can be claimed (or back-claimed) with your SkillsFuture Credit):

Interactive Python Dashboards with Plotly and Dash

Hands-On Natural Language Processing (NLP) using Python

Python for Data Science and Machine Learning Bootcamp

Programming for Everybody

These short courses enabled me to pick up basic coding skills and knowledge about data science. More importantly, I gained confidence in my ability to learn and started seeing the potential of data analytics beyond the industry I was familiar with.

Without them, I most certainly would have been unable to cope with more advanced courses.

Moving beyond self-learning, I considered taking a Masters in Analytics, but ultimately did not take that route due to costs and time as it would have taken at least a year and set me back by about $25,000.

Instead, I leaned towards coding bootcamps that were more affordable and could be completed in a few months.

Eventually, I chose General Assembly’s 12-weekData Science bootcampbecause of itsreputationand career services, which included career coaching and a “meet and greet” event with prospective employers.

If you’re Singaporean, embrace the monetary perks of citizenship! Manyonline coursesare claimable on SkillsFuture andsome are even free.

Two-thirds (that’s over $9,000) of my $14,500 bootcamp fee was also subsidised by the government (through anIMDA scheme).

Be prepared to be humbled.

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (5)

Going back to school is humbling. For 12 entire weeks, I found myself struggling with statistics, vectors and probability – concepts I thought I had left behind for good after my A levels.

But frankly, the toughest part of the career transition happened after I graduated.

I was sending out about 10 resumes a week and tweaking the accompanying cover letters to suit particular roles. Industry veterans back at General Assembly had warned us that 90 percent of applications would not receive a response but experiencing it first-hand was still a visceral gut punch.

A cursory check of data job openings on LinkedIn showed easily more than 200 applications per position, not surprising given the numerousdata bootcamps and Mastersprogrammesout there today.

Based on my job hunt, a STEM (science, technology, engineering, maths) background definitely helps. Some employers sent strong signals they would much rather be talking to engineers, statisticians, or computer programmers.

As someone without a STEM degree, I had to work doubly hard to demonstrate the requisite aptitude and overcome doubts about my technical ability. I was actually the last person in my cohort to land a job – at99.co, a real estate portal.

Half of my classmates who were sponsored to do the course went back to their jobs using their new-found data skills as an employability boost.

The others joined multinational companies, government bodies, and start-ups.

In many ways, my job search was also eye-opening.

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (6)

On one hand, I experienced the infamous and harrowing ‘whiteboard test’ where interviewers younger than myself pushed me to my limits (and were extremely encouraging, to their credit).

On the other, I was absolutely taken aback by an encounter with someone in a senior tech role who was oblivious to the most basic of tech and data concepts (imagine a biologist who had never heard of DNA).

It drove home the point that in today’s environment of rapid technological change, no one – no matter your seniority or designation – is exempt from lifelong learning.

I may have achieved a small measure of success in my career switch so far, but if I rest on my laurels, I can easily be made obsolete by those who are hungrier and armed with knowledge I don’t possess.

This may seem daunting, but I got my start in data analytics precisely because someone was willing to evaluate me based on whether I had the relevant skills and the capacity to learn, and not based on my seniority or a piece of paper I earned from university years ago.

And in this world where skills are king, anyone who is willing to learn has a fighting chance.

TWS: This is a future where people are paid more for their knowledge, skills and contribution, not how long they’ve clung on to the corporate ladder.

And it’s both a terrifying and exciting time to be alive.

Stay awake, salaryman

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I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman: (2024)

FAQs

I switched careers at 34 and became a Data Analyst. Here’s how. - The Woke Salaryman:? ›

As long as you've got the right skills, you can become a data scientist at any age.

Can I become data analyst at 35? ›

As long as you've got the right skills, you can become a data scientist at any age.

Is 35 too old for data science? ›

Whatever your age, it's never too late to pursue your dreams of becoming a qualified data scientist. Learn how to succeed in this profession below.

Am I too old to be a data analyst? ›

It's never too late to become a data scientist - as long as you've got the right skills and determination, you can become a data scientist at any age. Assuming you have the skillset, there isn't an age limit - even if you're starting from scratch with a degree.

Why you should not become a data analyst in 2023? ›

They also have to deal with a lot of difficult data, which can be overwhelming. Furthermore, data analysts often have to work with complex software that is constantly changing. So, if you look into an easy job, it is not!

What is the average age of a data analyst? ›

49.8% of all data analysts are women, while 50.2% are men. The average age of an employed data analyst is 43 years old.

Is data analyst a stressful job? ›

Data analysis is a stressful job. Although there are multiple reasons, high on the list is the large volume of work, tight deadlines, and work requests from multiple sources and management levels.

Is data science dead in 10 years? ›

By definition, “Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.” So, until and unless we find a way to not use data itself, data science as a field is not going to be obsolete anytime soon.

Can I master data science in 6 months? ›

Becoming a data scientist in six months is possible if you have a strong background in mathematics and coding. If you are one such candidate, follow the steps below: Download simple datasets and perform Exploratory Data Analysis on them.

Is 3 months enough for data science? ›

In the third month, when you are good at data analysis and machine learning, you are ready to start using the tools of a real-world environment recommended by expert data scientists.

Who should not become a data analyst? ›

This might seem like a no-brainer, but if you're not naturally comfortable working with data – you probably should not become a Data Analyst. The thing is if you're not a data person, you may not realize that some people are just born comfortable with using spreadsheets and have been on computers their entire life.

Is it difficult to get data analyst job with no experience? ›

In short: Data analysts are in high demand, putting newcomers in a great position. The jobs are there; as long as you've mastered (and can demonstrate) the right skills, there's nothing to stop you getting a foot in the door.

Are data analysts introverts? ›

Data Analyst

The path to becoming a data analyst requires good organizational and analytical skills while offering an independent working environment, making it one of the best career choices for introverts.

Why do data analysts quit? ›

There simply are not enough people with a background in analytics. That scarcity makes the data analyst role expensive and competitive to fill, and so easy for us to quit. Moreover, most analysts at the junior to mid-level know that the fastest path to higher salary is to switch companies.

What are the disadvantages of being a data analyst? ›

Limitations
  • Lack of alignment within teams. There is a lack of alignment between different teams or departments within an organization. ...
  • Lack of commitment and patience. ...
  • Low quality of data. ...
  • Privacy concerns. ...
  • Complexity & Bias.

How smart do you have to be to be a data analyst? ›

While data analysts should have a foundational knowledge of statistics and mathematics, much of their work can be done without complex mathematics. Generally, though, data analysts should have a grasp of statistics, linear algebra, and calculus.

Is data analyst a lot of math? ›

As with any scientific career, data analysts require a strong grounding in mathematics to succeed. It may be necessary to review and, if necessary, improve your math skills before learning how to become a data analyst.

How much do entry level data analysts make? ›

What is the total pay trajectory for Entry Level Data Analyst?
Job TitleSalary
Entry Level Data Analyst$53,656 /yr
Data Analyst$70,035 /yr
Senior Data Analyst$103,666 /yr

Is data analyst an IT job? ›

Data analysis is not necessarily an IT (information technology) job but requires working with IT tools and systems. Data analysis involves using statistical and computational techniques to derive insights from data, which can be applied in various industries such as healthcare, finance, marketing, and more.

How many hours does a data analyst work? ›

How Many Hours can a Data Analyst Expect to Work? Generally speaking, Data Analysts can expect to work between 40 and 60 hours a week, typically on a Monday through Friday schedule, which would correspond with the hours the business or company is open. This often means a 9-5 or 8-6 day.

Are data analysts happy with their job? ›

No, data analysts are generally not happy.In fact, data analysts rate their career happiness 2.9 out of 5 stars which puts them in the bottom 22% of careers, according to a 2022 U.S. News study.

Do data analyst code? ›

Do Data Analysts Code? Some Data Analysts do have to code as part of their day-to-day work, but coding skills are not typically required for jobs in data analysis.

Will data analyst be replaced by AI? ›

No. But it will redefine the data analyst role.

Since ChatGPT's release in November of 2022, speculation has grown over whether or not the role of a data analyst could eventually be replaced by generative AI (ChatGPT, Bard, and Bing Chat are among the large language models included in this classification).

Will AI replace data science? ›

Long answer short —AI models like Chat GPT can be a valuable tool for data scientists, but they cannot replace the important role that data scientists play in various industries. This is true for most of the roles.

Is data science the hottest job? ›

For the last four years, data science has been featured as a top career by Glassdoor. What's more, Harvard University has named a data scientist as the 'sexiest job title of the 21st century'.

Can I become a data scientist after 30? ›

Yes. Anyone aged 30 can furthermore apply for a data science job.

How long to master Python for data science? ›

Average Time it Takes to Learn Python for Data Science

Estimates for mastering data science range from six months to several years. However, you may be able to learn Python fundamentals in a few months—even less if you study full-time.

How long is a masters in data science at Harvard? ›

How Long Does it Take to Complete the Data Science Graduate Program? Program length is ordinarily anywhere between 2 and 5 years. It depends on your preferred pace and the number of courses you want to take each semester.

How long should you stay in a data science job? ›

How long do you expect to stay (from time you started) in your CURRENT analytics/data science job? had a median answer of about 3 years, and an average of 4.5 years. Among job types, we see big pull from industry and increase in self-employed, and decline in academia.

Can I become a data analyst in 3 months? ›

The 3-Month Journey to Becoming a Data Analyst. It takes effort to improve as a data analyst in just three months. However, success in data analysis requires focus and challenging endeavors. Following our guide will give you sufficient expertise over the next three months to launch a successful data analysis profession ...

How long does it take a data analyst to become a data scientist? ›

How long does it take to become a data scientist? As we outline in our data science FAQs, on average, to a person with no prior coding experience and/or mathematical background, it takes around 7 to 12 months of intensive studies to become an entry-level data scientist.

Is it worth being a data analyst in 2023? ›

In addition, data analyst education and skills open the door to several other career paths, including information security, market research, management, computer systems, and financial analytics—all among the top 25 careers according to the 2023 U.S. News's best jobs ranking.

What type of personality does a data analyst have? ›

The average Data Analyst is likely a natural problem-solver: Perceptive, analytical, and detail-oriented. The average Data Analyst tends to be confident and insightful, enjoying deep discussion to understand a particular issue.

Is data analyst a good career for 2023? ›

The demand for data analysts is on the rise, but so is the competition for jobs. By gaining specialized skills, building a strong network, gaining relevant industry experience, and customizing your application materials, you can increase your chances of landing a data analyst job in 2023.

How do I land my first data analyst job? ›

If you want to pursue a career as a data analyst, there are five main steps you'll need to take:
  1. Learn the essential data analysis skills.
  2. Gain a qualification that demonstrates these skills.
  3. Practice your data analyst skills on a variety of projects.
  4. Create a portfolio of your work.
  5. Apply for entry-level data analyst jobs.

Is Google data analytics Professional Certificate worth it? ›

In short, a great program to join, in fact the best Coursera course to learn Data Analytics and become a Data Analyst in 2023. That's all about review of Coursera's most popular, Google Data Analytics Professional Certificate in 2023.

What does an entry-level data analyst do? ›

What Does an Entry-Level Data Analyst Do? The job duties of an entry-level data analyst include working to collect, manage, and analyze data. In this career, your responsibilities often revolve around performing research on business or industry data to define trends or assess performance in a particular sector.

Are data analysts respected? ›

Skilled data analysts are some of the most sought-after professionals in the world. Because demand is strong and the supply of people who can do this job well is limited, data analysts command higher-than-average salaries and perks, even at the entry level.

Are data analysts customer facing? ›

This role is customer-facing centered, even if the 'customer' is internal.

Can a non technical person learn data analyst? ›

Data Science is only for persons with an IT background. It is a persistent myth that many people believe. Although it is true that some IT professionals seek to advance their skills in analytics, this field is not only open to people with a background in programming and IT.

What is the burnout rate for data analysts? ›

Burnout is a problem many data scientists face today. A recent study of nearly 600 data scientists found that 55% are experiencing high levels of work-related stress. Much of this stress comes from spending too much time maintaining data pipelines and manual processes and focusing on finding and fixing errors.

Will data analysts be replaced by computers? ›

AI won't replace data analysts partly because machines can't (yet) understand context like we can. They can't read a room and they can't adapt their storytelling to that room. You, the self-aware data storyteller will drive the future of business…. And your career simultaneously.

What is the biggest challenge of a data analyst? ›

Low-Quality Data

Inaccurate data is a major challenge in data analysis.

Is it too late to become a data analyst at 30? ›

Whatever your age, it's never too late to pursue your dreams of becoming a qualified data scientist.

Why is data analyst difficult? ›

Data analysis is neither a “hard” nor “soft” skill but is instead a process that involves a combination of both. Some of the technical skills that a data analyst must know include programming languages like Python, database tools like Excel, and data visualization tools like Tableau.

Is data analyst a hard or soft skill? ›

In order to be a successful data analyst, it's not enough to just have strong technical skills. Data analysts also need strong soft skills, such as communication and problem-solving skills. Data storytelling: One of the most important soft skills for data analysts is storytelling.

What do data analysts do all day? ›

Data analysts spend their workdays digging into big data and making it useable for the company they work for. This includes tasks like analyzing data systems, automating information retrieval and preparing reports that show managers how this data could be applied to their business model.

Can I work from home as a data analyst? ›

It is possible to obtain a job as a work from home data analyst with no experience, but most employers want candidates with a specific skill set and who do not need much training. Most positions require a bachelor's degree in statistics, mathematics, or a related field.

How long does it take to become a good data analyst? ›

The time commitment for college will depend on the degree you pursue, taking between four or five years to complete. Ultimately, however, the time it takes to become a data analyst depends on your commitment to learning and advancing your knowledge and career.

Can you become a data scientist in your 30s? ›

However, there's no reason why individuals can't begin work in data science later in their careers. In fact, it may even have its own unique benefits. Read on for five reasons why there's never a wrong time to learn data science.

How soon can I become a data analyst? ›

The time commitment for college will depend on the degree you pursue, taking between four or five years to complete. Ultimately, however, the time it takes to become a data analyst depends on your commitment to learning and advancing your knowledge and career.

How many months does it take to become a data analyst? ›

A bachelor's degree in a related field like statistics, computer science, or mathematics is required to become a data analyst. Obtaining a bachelor's degree can take around four years of full-time study. However, learning the necessary skills through self-study or a boot camp-style program is also possible.

Is 1 year enough for data science? ›

People from various backgrounds especially with zero coding experiences have proven to become good data scientists in just one year by learning to code smartly.

How do I transition to data analyst? ›

How to Become a Data Analyst With No Experience
  1. Understand where you want to go as a data analyst.
  2. Receive foundational training and understand which skills you need to acquire.
  3. Obtain the skills through a degree, bootcamp, or self-direct learning.
  4. Break into the chosen industry.

How do I shift to data analyst? ›

How to Become a Data Analyst (with or Without a Degree)
  1. Get a foundational education.
  2. Build your technical skills.
  3. Work on projects with real data.
  4. Develop a portfolio of your work.
  5. Practice presenting your findings.
  6. Get an entry-level data analyst job.
  7. Consider certification or an advanced degree.
Jun 15, 2023

Is data analytics a lot of math? ›

Data analytics requires a lot of skills that aren't just math, many of which you may already possess. And, with the right strategy, tools, and mindset, you can succeed at picking up the algebra and statistics you need to get started in the field.

How much Python is required for data analytics? ›

For data science, the estimate is a range from 3 months to a year while practicing consistently. It also depends on the time you can dedicate to learn Python for data science. But it can be said that most learners take at least 3 months to complete the Python for data science learning path.

Can an average person be a data scientist? ›

Data science is fully based on mathematics and statistics. If you are from the same background it will be easy to learn data science, and it will be easy to be a data scientist. If you are from a non-IT background, first you have to learn mathematics and statistics.

Is switching to data science worth it? ›

This field is among the best paid in the IT industry. And this is valid for any country around the world. The journey into data science can be very rewarding from a personal development perspective - you will learn mathematics, statistics, computer science, and will develop solid business understanding.

How long does it take for a beginner to become a good data scientist? ›

How long does it take to become a data scientist? As we outline in our data science FAQs, on average, to a person with no prior coding experience and/or mathematical background, it takes around 7 to 12 months of intensive studies to become an entry-level data scientist.

Is it hard to get hired as a data analyst? ›

In short: Data analysts are in high demand, putting newcomers in a great position. The jobs are there; as long as you've mastered (and can demonstrate) the right skills, there's nothing to stop you getting a foot in the door. CareerFoundry graduate Chad Stacey is a great example of this.

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