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Switch to Data Science from Accounting

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[OP]
Deal Addict
Jan 3, 2012
1266 posts
31 upvotes
Mississauga

Switch to Data Science from Accounting

Hello Everyone,

I'm currently 29 years old with almost 7 years of accounting and finance experience, and also working towards my CPA designation. In my 7 years, I have not only done accounting and FP&A, but also a lot of big data analysis/data manipulation/producing useful financial reports from raw data using excel, access, VBA and SQL. I'm currently working on further improving my VBA and SQL skills as I'm still a beginner in programming and never took any programming courses. All my programming knowledge of VBA and SQL is from google/youtube.

A month ago I heard about Data scientist job, and how its demand is increasing like crazy every year. I did a lot of thinking and realize that I have actually enjoyed data analysis more than accounting in my 7 years career, and thought perhaps working towards becoming data scientist would be much better for me than getting my CPA and stay in Accounting.

So I would like everyone's opinion whether or not this switch is a wise decision for me, and whether i will face difficulties in getting a Data scientist job. I know my competition will be with young 23 years old graduate with background in programming/computer science. So do i stand a chance? What should i do?

This is my action plan so far:

1) Drop CPA and enroll in Master in Data Science and Analytics program at Ryerson University
2) Start taking SQL, VBA, Python, Machine learning, SAS, R, and additional courses related to data science on website like Udemy, Coursera, DataCamp
3) Start doing projects on Kaggle.com once i feel comfortable with programming
4) Perhaps, attend conferences and seminars related to Data Science


I'm currently a Senior Financial Analyst, and my main duties do involve a lot of data analysis, and creating KPI/metrics from scratch using raw data, as well as automating reports using VBA and Access/SQL.
70 replies
Member
Dec 11, 2013
471 posts
359 upvotes
Toronto
This reads like you're trying to sell the idea, rather than option feedback.

Are you good at programming? Does it comes easily to you? Do you currently have any network that could open a door for one of those jobs?

Those are the questions you need to ask. If there was a massive demand for NHL hockey players, it still probably wouldn't help your chances of getting that job.
Deal Expert
Jan 27, 2006
17247 posts
10015 upvotes
Vancouver, BC
You won't stand a chance.

The courses on places like Udemy, Coursera, and DataCamp aren't any replacement for a degree in Computer Science. Most employers won't even know what those places are let alone what's covered in those courses on those sites. Even those 23 year old graduates won't really be in competition with anyone who knows or has a experience as a data scientist (that in itself isn't well defined so trying to patch together some kind of pathway using the resources your mentioned is laughable at best).
[OP]
Deal Addict
Jan 3, 2012
1266 posts
31 upvotes
Mississauga
craftsman wrote: You won't stand a chance.

The courses on places like Udemy, Coursera, and DataCamp aren't any replacement for a degree in Computer Science. Most employers won't even know what those places are let alone what's covered in those courses on those sites. Even those 23 year old graduates won't really be in competition with anyone who knows or has a experience as a data scientist (that in itself isn't well defined so trying to patch together some kind of pathway using the resources your mentioned is laughable at best).
These courses will be just for my own knowledge, employers won’t have to know. I will be doing a Master degree in Data science and analytics too. Plus I have experience working with big data, analyzing big data, manipulating and produce financial reports using raw data, automating and creating database.

Still I have no chance?
Deal Addict
Jul 7, 2013
1294 posts
976 upvotes
North York
Good luck OP! Everyone wants to jump on that ship from accounting from what I hear
Sr. Member
Dec 15, 2015
692 posts
504 upvotes
Toronto
SK_786 wrote:
I'm currently a Senior Financial Analyst, and my main duties do involve a lot of data analysis, and creating KPI/metrics from scratch using raw data, as well as automating reports using VBA and Access/SQL.
If this is your day to day, why are you going back to school? Can't you leverage your CPA and a background in programming to get where you want to be? Learn at home and apply it to your real world projects.
[OP]
Deal Addict
Jan 3, 2012
1266 posts
31 upvotes
Mississauga
TheMaterial wrote: If this is your day to day, why are you going back to school? Can't you leverage your CPA and a background in programming to get where you want to be? Learn at home and apply it to your real world projects.
Yes I can but almost all data scientist job that I saw on LinkedIn requires a Master degree. My plan is to continue working full time, start Master program part time, and further improve my skills thru online courses on python, machine learning etc
Jr. Member
Dec 21, 2009
177 posts
112 upvotes
Oakville
SK_786 wrote: Hello Everyone,

I'm currently 29 years old with almost 7 years of accounting and finance experience, and also working towards my CPA designation. In my 7 years, I have not only done accounting and FP&A, but also a lot of big data analysis/data manipulation/producing useful financial reports from raw data using excel, access, VBA and SQL. I'm currently working on further improving my VBA and SQL skills as I'm still a beginner in programming and never took any programming courses. All my programming knowledge of VBA and SQL is from google/youtube.

A month ago I heard about Data scientist job, and how its demand is increasing like crazy every year. I did a lot of thinking and realize that I have actually enjoyed data analysis more than accounting in my 7 years career, and thought perhaps working towards becoming data scientist would be much better for me than getting my CPA and stay in Accounting.

So I would like everyone's opinion whether or not this switch is a wise decision for me, and whether i will face difficulties in getting a Data scientist job. I know my competition will be with young 23 years old graduate with background in programming/computer science. So do i stand a chance? What should i do?

This is my action plan so far:

1) Drop CPA and enroll in Master in Data Science and Analytics program at Ryerson University
2) Start taking SQL, VBA, Python, Machine learning, SAS, R, and additional courses related to data science on website like Udemy, Coursera, DataCamp
3) Start doing projects on Kaggle.com once i feel comfortable with programming
4) Perhaps, attend conferences and seminars related to Data Science


I'm currently a Senior Financial Analyst, and my main duties do involve a lot of data analysis, and creating KPI/metrics from scratch using raw data, as well as automating reports using VBA and Access/SQL.
I came from a simliar background as you - VBA, SQL - Finance Background.

Don't do pure Data Science, do Analytics and Strategy with client facing experience, its mostly the same, more career progression, and more money as you move up to ladder.

I'd still recommend learning R, SAS and SQL is a must, but more so understand the logic behind why you would use certain models for what.

Twist your current experience of Requirement gathering, strategic insights generation for internal teams, model preperation, KPI frameworks, automation, deck preperation, presentations, client facing, etc -

Then just go to indeed.ca look for roles under analytics & strategy, analytics & insights, etc etc

If you can understand Data Science techniques/models and have the Business Acumen/Client facing capabilities you can go far, typically what I've seen is pure data scientist don't have the acumen to deal with the client or develop strategy.

But to do all is even better.
Deal Expert
Jan 27, 2006
17247 posts
10015 upvotes
Vancouver, BC
SK_786 wrote: These courses will be just for my own knowledge, employers won’t have to know. I will be doing a Master degree in Data science and analytics too. Plus I have experience working with big data, analyzing big data, manipulating and produce financial reports using raw data, automating and creating database.

Still I have no chance?
One thing I've learned about Masters degrees - they work well in developed fields but are often behind (but not always) in developing or growth fields. Big data is one of those fields that is growing fast. Since much of the grunt work will need to be automated in order to work through a lot of the large data sets, much of that automation will be done by the computer science grads/programmers/developers. A masters will give you more of an architect view of things. What area of data science are you looking to get into? If it's architecture, you will still have a hard go at it as many employers would rather get someone that has a lot of hard earned experience in the field over someone with just a degree. If it's at the ground floor and moving upwards, you will have stiff competition from computer science grads/programmers/developers doing the grunt work and most people won't hire masters grads for grunt work and they already have architects.

Your best bet would be if you want to continue down this road is to add a programming diploma then follow that up with the masters so that your resume will have your masters first and the diploma to show that you have some programming skills to back the masters up.
Deal Fanatic
Sep 23, 2007
5061 posts
1159 upvotes
SK_786 wrote: These courses will be just for my own knowledge, employers won’t have to know. I will be doing a Master degree in Data science and analytics too. Plus I have experience working with big data, analyzing big data, manipulating and produce financial reports using raw data, automating and creating database.

Still I have no chance?
I can speak first hand about data work with my experiences at 2 companies.

Data science is quite new. In one company, they hired someone to do data work and it blossomed into a department by itself. She got a team of 2 people under her.

In another company, the "data work" function fell into finance. Companies are most interested in sales data depending on company structure, a lot of data work falls back on finance/accounting staff.

In both companies the data work is quite different. In the first one, they specifically hired people to work with data like data cleansing, using Excel to validate completeness etc. In the 2nd one, it's more of a hybrid role. A mix of data work and financial reporting. So I guess it boils down to how badly the company needs data. Accounting is a core function. If data matters a lot, it's likely they hire dedicated data staff. If data is not critical, it tends to fall back onto finance/accounting staff.

I can tell you in both companies, very few macros were used. There's an IT aspect of it where the IT team create a data cube for you to load. Then you just build templates to make sure the data is in the right format to load into the cube.
Deal Addict
Nov 14, 2010
1087 posts
195 upvotes
The question is why do you want to switch from accounting and business? You seem to be doing well there.

Do you know who your competition is? Math, stats, and hard science/engineering PhDs who couldn't make the tenure track but are more than qualified to handle all of the problems in this discipline. Those are the people that will be interviewing you as well. I'm sorry to say, but the perception of most in the business field is one of incompetence, extreme difficulty with numbers, and your only redeeming qualities are "soft skills" and playing the office politics game. It may be incredibly unfair, but that's the perception. There once was a time where a financial analyst could sell themselves easily to companies as a data scientist and many companies were burned hard and have wised up.

Don't waste your time and money on those master's programs. All they will give you is a superficial level of the knowledge and skills required at best. You may be able to regurgitate some advanced concepts and may even seem like an expert who knows what they're doing to the people at HR, but the hiring manager will know rather quickly that you are way in over your head.

I am not saying its impossible. But you will have to stand out and be exceptional relative to the competition because it's rather quite simple to reach back into the resume pile and find a PhD who can easily transition into the position and produce useful work almost immediately.
Deal Addict
Nov 22, 2009
2642 posts
518 upvotes
Toronto
Metagame wrote: I am not saying its impossible. But you will have to stand out and be exceptional relative to the competition because it's rather quite simple to reach back into the resume pile and find a PhD who can easily transition into the position and produce useful work almost immediately.
I've noticed there are many with only a bachelor of mathematics or even masters that are currently data scientists on linkedin. I don't know if PhD is the minimum requirement.

https://www.linkedin.com/in/amir-ghaderi-650a2aaa/

https://www.linkedin.com/in/mezbah-uddin/

In fact, there's a whole list of people with a Masters in data science from Ryerson doing data science work.

https://www.linkedin.com/school/ryerson ... %20science

I'm not say it's easy, but you sound like only those with a PhD (bare minimum) in Engineering/Mathematics can get data science jobs...
Sr. Member
Feb 19, 2017
622 posts
367 upvotes
BananaHunter wrote: I can speak first hand about data work with my experiences at 2 companies.

Data science is quite new. In one company, they hired someone to do data work and it blossomed into a department by itself. She got a team of 2 people under her.

In another company, the "data work" function fell into finance. Companies are most interested in sales data depending on company structure, a lot of data work falls back on finance/accounting staff.

In both companies the data work is quite different. In the first one, they specifically hired people to work with data like data cleansing, using Excel to validate completeness etc. In the 2nd one, it's more of a hybrid role. A mix of data work and financial reporting. So I guess it boils down to how badly the company needs data. Accounting is a core function. If data matters a lot, it's likely they hire dedicated data staff. If data is not critical, it tends to fall back onto finance/accounting staff.

I can tell you in both companies, very few macros were used. There's an IT aspect of it where the IT team create a data cube for you to load. Then you just build templates to make sure the data is in the right format to load into the cube.
This only happens at smaller companies (keep in mind even "big" Canadian companies are actually just small companies globally) or for companies that do not have a lot of transactional data (non-customer facing usually).
None of what you are talking about is really considered data science type work.

Back to OP:
If you truly have an interest, then do it. Based on the fact you are 7 years into your accounting career, but still don't have your CPA yet, I'm guessing you are only making an average salary less than 100K. Here's my advice:
-Aim for work at a US company. Not only will they pay more, they are less likely to discriminate against your background because (1) they need tons of people who are good at working with data whereas Canadian companies are small and usually only need like 2-3 people so they will be super selective, (2) it is a skills based economy so as long as you can write the language up to their standards, they don't care what your background is, (3) because companies are bigger, you will get more data to work with.
-Apply to a respectable MAsters program at a good US school or at least a top Canadian school at a place like Waterloo.
-forget VBA...focus on SQL, Python, R, SAS, tableau, cloud data structures and platforms (hadoop, aws, azure, etc), machine learning...
-do side projects if you have time

Keep in mind that none of this is considered programming and the work you do will be very different from that of a software developer.

There is also a big difference between the people who work with the data (Business Intelligence Analysts/Engineers, Business Analysts, etc) and true data research scientists (usually someone with a highly specialized skill set or PhDs). Both can be heavily involved in big data type work, but there are not many of the latter, even in huge companies.
Deal Addict
Nov 14, 2010
1087 posts
195 upvotes
blitzforce wrote: I've noticed there are many with only a bachelor of mathematics or even masters that are currently data scientists on linkedin. I don't know if PhD is the minimum requirement.

https://www.linkedin.com/in/amir-ghaderi-650a2aaa/

https://www.linkedin.com/in/mezbah-uddin/

In fact, there's a whole list of people with a Masters in data science from Ryerson doing data science work.

https://www.linkedin.com/school/ryerson ... %20science

I'm not say it's easy, but you sound like only those with a PhD (bare minimum) in Engineering/Mathematics can get data science jobs...
No, that's not what I said. The preference is for PhDs, but someone with an MS or even bachelors with significant programming background, research projects/theses, etc. would definitely have options. The PhD's advantage is its inherently confers to prospective employers you know how to handle assignments and problems with no known solution. That still doesn't mean an accounting/finance/business grad is on equal footing with a math/stats/CS/engineering grad. One cohort is considered trainable while the other, in most cases, shouldn't even bother applying.
Deal Addict
Nov 22, 2009
2642 posts
518 upvotes
Toronto
Metagame wrote: No, that's not what I said. The preference is for PhDs, but someone with an MS or even bachelors with significant programming background, research projects/theses, etc. would definitely have options. The PhD's advantage is its inherently confers to prospective employers you know how to handle assignments and problems with no known solution. That still doesn't mean an accounting/finance/business grad is on equal footing with a math/stats/CS/engineering grad. One cohort is considered trainable while the other, in most cases, shouldn't even bother applying.
If he gets a masters in data science, I honestly don't understand how he is any different from the other people with masters in data science in linkedin. If he decides and go back to get a masters in stats in university, how would he be less qualified?

My friend was a finance grad, and he went back to school to get an engineering degree so not sure.
[OP]
Deal Addict
Jan 3, 2012
1266 posts
31 upvotes
Mississauga
Walch1102 wrote: This only happens at smaller companies (keep in mind even "big" Canadian companies are actually just small companies globally) or for companies that do not have a lot of transactional data (non-customer facing usually).
None of what you are talking about is really considered data science type work.

Back to OP:
If you truly have an interest, then do it. Based on the fact you are 7 years into your accounting career, but still don't have your CPA yet, I'm guessing you are only making an average salary less than 100K. Here's my advice:
-Aim for work at a US company. Not only will they pay more, they are less likely to discriminate against your background because (1) they need tons of people who are good at working with data whereas Canadian companies are small and usually only need like 2-3 people so they will be super selective, (2) it is a skills based economy so as long as you can write the language up to their standards, they don't care what your background is, (3) because companies are bigger, you will get more data to work with.
-Apply to a respectable MAsters program at a good US school or at least a top Canadian school at a place like Waterloo.
-forget VBA...focus on SQL, Python, R, SAS, tableau, cloud data structures and platforms (hadoop, aws, azure, etc), machine learning...
-do side projects if you have time

Keep in mind that none of this is considered programming and the work you do will be very different from that of a software developer.

There is also a big difference between the people who work with the data (Business Intelligence Analysts/Engineers, Business Analysts, etc) and true data research scientists (usually someone with a highly specialized skill set or PhDs). Both can be heavily involved in big data type work, but there are not many of the latter, even in huge companies.
How easy is it to get a job in US in data analytics field? Do you think getting my CPA plus learning about SQL, Python, R, SAS, tableau, cloud data structures and platforms (hadoop, aws, azure, etc), machine learning would help and make me a stronger candidate?
[OP]
Deal Addict
Jan 3, 2012
1266 posts
31 upvotes
Mississauga
Thank you for the advise everyone. It really is a tough decision, especially dropping CPA and enrolling in Master in Data Science and Analytics program.

What I'm now thinking is to continue with my CPA, and also start learning about SQL, python, R, SAS, tableau etc on side. Do you guys think combination of accounting and data science skills will help me? I will also aim of Senior business analyst or Senior data analyst roles next year. As these roles do not require PHD/Masters, and switch from accounting is easier. And I already have decent experience in data analytics, and know SQL and VBA.
Sr. Member
Feb 19, 2017
622 posts
367 upvotes
SK_786 wrote: How easy is it to get a job in US in data analytics field? Do you think getting my CPA plus learning about SQL, Python, R, SAS, tableau, cloud data structures and platforms (hadoop, aws, azure, etc), machine learning would help and make me a stronger candidate?
In the US, it's actually fairly easy to get interviews at big tech companies if you have a masters in data analytics or something similar from a good US school. Whether you get hired will depend on skill as all interviews at big tech firms are very technical.
CPA is fairly useless for data work.

It's really up to you. Go with the status quo and do data work for some small, uninspiring Canadian company or take the plunge and do a US masters. Even if you choose to come back to Canada, you'll have a better chance at landing a gig with Google, shopify, etc. in Toronto with some US exp.
Jr. Member
Dec 21, 2009
177 posts
112 upvotes
Oakville
SK_786 wrote: Thank you for the advise everyone. It really is a tough decision, especially dropping CPA and enrolling in Master in Data Science and Analytics program.

What I'm now thinking is to continue with my CPA, and also start learning about SQL, python, R, SAS, tableau etc on side. Do you guys think combination of accounting and data science skills will help me? I will also aim of Senior business analyst or Senior data analyst roles next year. As these roles do not require PHD/Masters, and switch from accounting is easier. And I already have decent experience in data analytics, and know SQL and VBA.
You can apply to these roles now and you may have a decent chance.

#1) Change your resume experience to more business insights/analysis experience. (frameworks, time series forecasting, customer segmentation, customer life time value, profitability analysis, optimization analysis, campaign measurement, etc)
#2) SQL most important, R/SAS knowledge helps for enterprise analytics and statistical analysis
#3) Apply to Sr Analyst roles, like Sr Analyst, Client analytics, strategy and analytics, marketing analytics, etc, etc.
#4) Learn how to ace the interviews
#5) Try to learn basic machine learning form business perspective (when to use clustering, regression, forecasting, etc)

I don't think CPA will help you much, it'll leave you in the FP&A, Reporting, Audit field... unless you wanna try and parlay that into finance
Jr. Member
Apr 30, 2017
128 posts
52 upvotes
I'm sure you've looked into the prerequisite of the master's program at Ryerson - that is, university/college level courses on R, basic computer science courses etc. Ryerson lists 3 courses as entry requirements, but one of those 3 courses has two courses as prerequisites, meaning if you don't have computer science background, you will likely have to take a total of 5 courses from Ryerson before you can apply for the master's program.

I am also considering a career change to data science, and my background is in biology, and am feeling slightly discouraged when I realized the amount of preparation I will need before I can even apply to the program.

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