Switch to Data Science from Accounting

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).

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.

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.

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.

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?

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?

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.

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.

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...

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.

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.

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?

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.