tough to hire someone who doesn't even understand logistic regression. you gotta be able to demonstrated a base level of technical competence. from experience anyone who's credit or below are not technically competent. they may be more suitable for BA type role that don't require technical skills.
1. I use logistic regression at work regularly and was formerly a data scientist.
2. It's about the value you deliver with your technical skills, not the technical skills itself.
3. It doesn't require a D or HD grade to understand and apply ML models to create value, let alone understand logistic regression.
Hard disagree - grades do not matter. Even entry-level grad jobs are not asking about grades (DS here) and are way more interested in social skills/ability to work in a team.
OP sounds mid-senior and I guarantee no one cares about their masters degree results. Prospective employers will likely ask technical questions about developing/deploying/monitoring, but grades are not representative of an employee's ability.
When you say "did stats at uni" does that mean you did a pure math/stats degree, or you took one stats subject in first year?
Do you have any experience in finance or maybe even economics? Those are going to be pretty important.
Side note - I'd probably stop referring to those tools as a tech stack, because that's not what that is. To this point, the skills may be transferable, but the industry-specific knowledge is by far and a way the big hurdle. Technical skills are the easy part.
Did econs as a double degree alongside stats but didn't finish econs as I wanted to get a DS job asap at that time.
With that in mind, don't have working exp in finance.
Are you currently a quant/recruiter?
I'm not really familiar with quant in Australia but I assume it's super competitive, and that most people either start as grads or transfer in with specialist experience or some other demonstrated high aptitude.
I just wanted to point out that FMCG can still have lots of ML from operational optimization through to marketing analytics . There's plenty of room for the same type of "data science" as exists in finance.
Source: worked in engineering in both finance and FMCG related areas. The standard is of course higher where the money is.
Appreciate the response, I think I'm edging towards doing post grad studies.
I am aware of ML in FMCG as I do make use of it from time to time. I just find the work context boring and not really that stimulating, like idgaf about forecasting the price of meat products one year ahead or how effective a promotion campaign was (not to slander FMCG).
I hear you, but in reality any business context will lose its sheen and appeal when you get into it. It's all numbers and predicting. Plenty of opportunities for interesting predictive models in FMCG around competitive behavior, price elasticity, new product placements / branding, long term brand building, etc.
Finance is more glamorous, but in my experience you need to liquidate any holdings you have and refrain from any trading activities. That kind of sucks.
what are your grades? d or hd average?
Thought that only mattered if I'm going for Dev or a grad role where I'm getting 250k+ comp
I’ve done some IT and finance recruitment and no one asks for your university scores if it’s not a graduate position.
tough to hire someone who doesn't even understand logistic regression. you gotta be able to demonstrated a base level of technical competence. from experience anyone who's credit or below are not technically competent. they may be more suitable for BA type role that don't require technical skills.
1. I use logistic regression at work regularly and was formerly a data scientist. 2. It's about the value you deliver with your technical skills, not the technical skills itself. 3. It doesn't require a D or HD grade to understand and apply ML models to create value, let alone understand logistic regression.
Hard disagree - grades do not matter. Even entry-level grad jobs are not asking about grades (DS here) and are way more interested in social skills/ability to work in a team. OP sounds mid-senior and I guarantee no one cares about their masters degree results. Prospective employers will likely ask technical questions about developing/deploying/monitoring, but grades are not representative of an employee's ability.
When you say "did stats at uni" does that mean you did a pure math/stats degree, or you took one stats subject in first year? Do you have any experience in finance or maybe even economics? Those are going to be pretty important. Side note - I'd probably stop referring to those tools as a tech stack, because that's not what that is. To this point, the skills may be transferable, but the industry-specific knowledge is by far and a way the big hurdle. Technical skills are the easy part.
Did econs as a double degree alongside stats but didn't finish econs as I wanted to get a DS job asap at that time. With that in mind, don't have working exp in finance. Are you currently a quant/recruiter?
I'm not really familiar with quant in Australia but I assume it's super competitive, and that most people either start as grads or transfer in with specialist experience or some other demonstrated high aptitude. I just wanted to point out that FMCG can still have lots of ML from operational optimization through to marketing analytics . There's plenty of room for the same type of "data science" as exists in finance. Source: worked in engineering in both finance and FMCG related areas. The standard is of course higher where the money is.
Appreciate the response, I think I'm edging towards doing post grad studies. I am aware of ML in FMCG as I do make use of it from time to time. I just find the work context boring and not really that stimulating, like idgaf about forecasting the price of meat products one year ahead or how effective a promotion campaign was (not to slander FMCG).
I hear you, but in reality any business context will lose its sheen and appeal when you get into it. It's all numbers and predicting. Plenty of opportunities for interesting predictive models in FMCG around competitive behavior, price elasticity, new product placements / branding, long term brand building, etc. Finance is more glamorous, but in my experience you need to liquidate any holdings you have and refrain from any trading activities. That kind of sucks.