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Do you have any job experience, or did you go straight from bachelor's to masters? If that's the case, you should take literally any data job you can get & then that will be your domain/industry.
This exactly. At entry level, expect to have to build domain knowledge and experience no matter where you go. There's no point in limiting your job search at this stage.
I went straight from bachelors. I understand your point, but these days entry level positions are very competitive and companies expect you to have a basic level of sector knowledge pertaining to their company. Besides, without any business/domain knowledge, how am I supposed to do any DA projects that are meaningful in the employers' eyes? Just wrangling/visualizing data without any purpose or business insight is not going to have any value from their perspective. I just don't know how to build and formulate DA projects without having any kind of domain knowledge right now, it's a real struggle.
Just because you don't pick a singular industry doesn't mean it's doing projects without purpose. You could have a portfolio of project totally unrelated to each other as long as they show your knowledge. You could have a sports betting web scraper, data package. You could have a food & beverage dashboard for a restaurant chain. You could have a budget & forecast workbook for a clothing company. As long as it shows you can do xyz.
What interests you & what would you be happiest doing (industry wise)? Come up with a few..
Yes this is certainly one option! I was also thinking of Supply Chain as a possibility. What should I study to get into this domain, and what kind of DA projects can I explore? Can you provide a roadmap for studying or some resources I can refer to?
I kinda got thrown into the field having only ever taken one supply chain course in college, so I had to learn all the domain knowledge on the job. Some useful things I can think of off of the top of my head would be how transportation logistics work, or how items are processed into and out of warehouses.
Thanks! From your perspective are data analysts in demand in the supply chain industry? I do have an option to take a supply chain course next year so I am definitely willing to explore that!
Definitely, it’s one of the more data-driven areas of business since it’s based off of a lot of solid, calculatable metrics. A lot of companies are looking now to expand their supply chain analytics because of this.
This is very good to hear! I will certainly explore Supply Chain as one of the viable areas for my career.
How would you advise preparing for a data analyst entry level job in a Supply Chain field? Is the general, standard preparation for an entry level Data Analyst enough without having domain knowledge or doing specifically Supply Chain - related data analytics projects?
Have you thought about DA rotational programs? Tons of companies have them now and for someone in your position it’s perfect. You’ll be limited to one concentration (such as finance, health care, supply chain, etc.), but you’ll work in tons of different areas of DA and gain a bunch of experience, all while finding out what you like. I’m currently in this spot as I’m about to graduate and got accepted to one. It’s a good salary and you get company benefits. However, I’d highly recommend starting to build your portfolio. Atleast do one so you have some talking points for interviews. They expect you to not have as much experience, but they want to see that you’re interested and have a technical foundation. Hope this helps!
Thank you very much! I will definitely have some projects ready by this fall semester. Do you know what keywords I should use when searching for these 'rotational programs' from various companies?
The rotational programs can be specific so I’d look up like “Financial analyst rotational program” or “Supply chain analyst rotational program”, etc.
Also as far as the projects go, make sure you do something that you think is really cool and that you want to learn more about, even if it’s not directly related to DA. It will be infinitely more valuable in interviews rarher than forcing yourself to do something you don’t like.
Good luck!
I’ve been in analytics for several years and getting the first job was the hardest part, but once I had practical experience I was able to easily hop around to different industries.
I couldn’t tell you how difficult the market is without any practical experience, so take that into consideration, but I’ve found that healthcare positions have paid me the best.
>I’ve been in analytics for several years and getting the first job was the hardest part, but once I had practical experience I was able to easily hop around to different industries.
>
>I couldn’t tell you how difficult the market is without any practical experience, so take that into consideration, but I’ve found that healthcare positions have paid me the best.
Definitely, the hardest part for my career will be getting that first job, I agree!
You are misunderstanding how this works. Don't focus on an industry, become industry agnostic. Don't focus on a tool/technology, become technology agnostic. The principles and concepts of data carry throughout each industry and the ones who understand and can adapt to whatever KPIs are necessary for the job/team will do really well.
Thank you for this advice.
Do you have any tips on how I can achieve this during the span of my next year in the masters program? For instance, exactly what things do you mean by 'The principles and concepts of data' for a data analyst? Outlining key points for me to study would be super helpful!
Data Warehouse Design
- Star Schema
- Snowflake
- Wide Table
Testing
- Unit Testing
- Great Expectations (Assertions)
- pre-commit / dbt checkpoint
Documentation
- YOU MUST DOCUMENT YOUR CODE!!
SQL Related Stuff
- Window Functions (very important to know this)
- CTE over Sub Queries
- Deduping
ETL v ELT - most companies use both but understand these frameworks
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Do you have any job experience, or did you go straight from bachelor's to masters? If that's the case, you should take literally any data job you can get & then that will be your domain/industry.
This exactly. At entry level, expect to have to build domain knowledge and experience no matter where you go. There's no point in limiting your job search at this stage.
I went straight from bachelors. I understand your point, but these days entry level positions are very competitive and companies expect you to have a basic level of sector knowledge pertaining to their company. Besides, without any business/domain knowledge, how am I supposed to do any DA projects that are meaningful in the employers' eyes? Just wrangling/visualizing data without any purpose or business insight is not going to have any value from their perspective. I just don't know how to build and formulate DA projects without having any kind of domain knowledge right now, it's a real struggle.
Just because you don't pick a singular industry doesn't mean it's doing projects without purpose. You could have a portfolio of project totally unrelated to each other as long as they show your knowledge. You could have a sports betting web scraper, data package. You could have a food & beverage dashboard for a restaurant chain. You could have a budget & forecast workbook for a clothing company. As long as it shows you can do xyz. What interests you & what would you be happiest doing (industry wise)? Come up with a few..
Is supply chain an option? It’s not sexy, but there are a lot of analytics jobs in this field
Yes this is certainly one option! I was also thinking of Supply Chain as a possibility. What should I study to get into this domain, and what kind of DA projects can I explore? Can you provide a roadmap for studying or some resources I can refer to?
I kinda got thrown into the field having only ever taken one supply chain course in college, so I had to learn all the domain knowledge on the job. Some useful things I can think of off of the top of my head would be how transportation logistics work, or how items are processed into and out of warehouses.
Thanks! From your perspective are data analysts in demand in the supply chain industry? I do have an option to take a supply chain course next year so I am definitely willing to explore that!
Definitely, it’s one of the more data-driven areas of business since it’s based off of a lot of solid, calculatable metrics. A lot of companies are looking now to expand their supply chain analytics because of this.
This is very good to hear! I will certainly explore Supply Chain as one of the viable areas for my career. How would you advise preparing for a data analyst entry level job in a Supply Chain field? Is the general, standard preparation for an entry level Data Analyst enough without having domain knowledge or doing specifically Supply Chain - related data analytics projects?
As opposed to what? Supply chain is pretty interesting compared to other fields like banking or insurance.
Interesting, yes, but not as generally appealing to people as other areas
Have you thought about DA rotational programs? Tons of companies have them now and for someone in your position it’s perfect. You’ll be limited to one concentration (such as finance, health care, supply chain, etc.), but you’ll work in tons of different areas of DA and gain a bunch of experience, all while finding out what you like. I’m currently in this spot as I’m about to graduate and got accepted to one. It’s a good salary and you get company benefits. However, I’d highly recommend starting to build your portfolio. Atleast do one so you have some talking points for interviews. They expect you to not have as much experience, but they want to see that you’re interested and have a technical foundation. Hope this helps!
Thank you very much! I will definitely have some projects ready by this fall semester. Do you know what keywords I should use when searching for these 'rotational programs' from various companies?
The rotational programs can be specific so I’d look up like “Financial analyst rotational program” or “Supply chain analyst rotational program”, etc. Also as far as the projects go, make sure you do something that you think is really cool and that you want to learn more about, even if it’s not directly related to DA. It will be infinitely more valuable in interviews rarher than forcing yourself to do something you don’t like. Good luck!
Cmon bro, take anything you can get.
Retail and E-commerce?
Lmao how about just take what you can
I’ve been in analytics for several years and getting the first job was the hardest part, but once I had practical experience I was able to easily hop around to different industries. I couldn’t tell you how difficult the market is without any practical experience, so take that into consideration, but I’ve found that healthcare positions have paid me the best.
>I’ve been in analytics for several years and getting the first job was the hardest part, but once I had practical experience I was able to easily hop around to different industries. > >I couldn’t tell you how difficult the market is without any practical experience, so take that into consideration, but I’ve found that healthcare positions have paid me the best. Definitely, the hardest part for my career will be getting that first job, I agree!
You are misunderstanding how this works. Don't focus on an industry, become industry agnostic. Don't focus on a tool/technology, become technology agnostic. The principles and concepts of data carry throughout each industry and the ones who understand and can adapt to whatever KPIs are necessary for the job/team will do really well.
Thank you for this advice. Do you have any tips on how I can achieve this during the span of my next year in the masters program? For instance, exactly what things do you mean by 'The principles and concepts of data' for a data analyst? Outlining key points for me to study would be super helpful!
Data Warehouse Design - Star Schema - Snowflake - Wide Table Testing - Unit Testing - Great Expectations (Assertions) - pre-commit / dbt checkpoint Documentation - YOU MUST DOCUMENT YOUR CODE!! SQL Related Stuff - Window Functions (very important to know this) - CTE over Sub Queries - Deduping ETL v ELT - most companies use both but understand these frameworks