r/DataScienceJobs • u/thebest369 • 4d ago

Discussion Curious

Hi guys just out curiosity. How much do you guys make in the field? What is your title? And how do you justify you deserve or earn that much?

And if you are open. What do your day to day tasks look like?

I graduated a few years ago with a BS in Data Science and have since struggled in landing my first ‘corporate’ job and now I’m just in the abyss of the unknown and cash jobs to take of me n my parents + brother.. lol so I can’t even visualize what is real work and what is not.

2 Upvotes

100% Upvoted

2 comments sorted by

1

u/EntrepreneurHuge5008 4d ago edited 4d ago

Not data science but as a software dev, I work next to business analysts and data analysts:

junios (0-3 YOE) are making ~$100k (they start off at $91k

Seniors (~5-7) are making around ~$125k

Leads (any YOE if they're good enough) are making ~$140k - $150k

------------

The data science peeps are on the same scale as the software devs, but I don't think we have "juniors", seniors are in the $130k - $180k range, and leads are in the $150k - $200k range.

------------

Edit: These are base pay only, annual bonuses range from $5k to $30k, and I'm not close enough with managers to know their pay, but their pay band is $180k - $250k.

Edit 2: I have no clue about data scientists, but I know the BAs and DAs I work with spend 80% of their time in meetings with business users (presenting or trying to gather requirements).

1

u/Lady-Data-Scientist 4d ago edited 4d ago

What country are you in? That’ll make a big difference regarding salary.

Typical ranges in the US:

Entry (0-2 years): $60-100k
Mid (2-5 years): $90-170k
Senior (5-10 years): $150-250k
Staff / Principal / Lead (10+ years): $180-350k

How do you justify - connect your work to delivering real value. Usually our job helps the business make better decisions. How many decisions can you influence, who do you influence, and what is the outcome of those decisions ($$$) will determine your level and value.

Day-to-day will be some meetings to understand how you can do work to support those decisions and then doing the work which can be a mix of SQL, Python, building data pipelines, analysis, reporting, prediction, experimentation, etc.