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Hi Everyone,
We are looking for Data Scientists
Experience: 2-8 years
Skills: Machine Learning, Deep Learning, Neural Networks, Regression, Random Forest, Clustering, XGBoost
Location: PAN India
If you are interested looking for change please share your resumes to priyanshi@mastermined.in
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Data scientist = SDE+ ML + DL +Devops + SDET + Data Analyst + Data engineering +BI + Research
5 years back people in interview generally asks python and little bit statistics..
3 yrs back people started asking for deep learning experience.
Now, it is combination of above all.
Exactly what I was about to say. Don't expect organizations will have plenty of data science work. Orgs use data science as an extension of their data architecture. I had started as Data Integration specialist, learned business Intelligence over the time, more than 10 dedicated tools for data engineering, data analytics, data reporting. Now I have started advanced data analytics and ML and in next 10 months will start deep learning.
If you just start as data scientist, don't expect you will go over data analyst salary. It is long learning curve and experience that matters to keep yourself motivated (in any tech stack)
I worked in a legacy technology for about 7 years. Resigned and did masters in Canada.
Pursued courses related to ML AI in my Masters. Have been doing online courses as well. Recently got Data Science offer in Canada.
I won't leave this field in my life. I spent lot of my time learning Python, SQL, Statistics, ML, Deep Learning, Analytics, Cloud etc.
I know that after joining the job, i won't be using all these tech skills. I might do some reporting work as well.
But, with the amount of time and efforts I spent learning things, I am going to teach the courses in my own style. This will help me to revise everything, stay updated with the recent trends in ML/Deep learning and ofcourse will help me to perform any task in my job.
The single source of inspiration for all this is, Andrew Ng's Machine Learning course.
Bhai Abhi start kiya hai data science course. Kyu demotivate Kar rhe😕
I am also thinking of joining data science course. Any suggestion from whr i shud do??
One thing about being in Data Science field is that you don't get much production experience as most of the time you find yourself working on some POC. At a point, it becomes boring leaving you wanting for more. And skill wise you don't really get to learn much. Your growth becomes stagnant. I feel for many businesses out there, Data Science is still luxury and less of a core requirement.
Also I feel that, at the end you may become Head of Data Science department in a company but you will still be reporting to some engineering manager or CTO.
This has been my experience. Yours may differ.
I started my career as SDE and then moved to ML field and now making efforts to move back to engineering.
Free advice:
If possible, be SDE or if you really want to be in data science, better be a ML Engineer so you can focus more on ML infra and service and less on model building, data cleaning and feature engineering.
Enjoy!
You said it bro. I have been doing POCs and pilot projects for 5 years now. And when people ask me what I have learnt as a data scientist in the last 5 years, I have little to tell them, and I am talking about real DS skills that could help in interviews.
Problem is with the expectations some companies have for a Data Scientist. They want us to be a SDE, DevOps, Data Engineer, Statistician, and of course Data Scientist at the same time.
This is so true, initially I thought Data Scientist just develops models using some libraries by understanding data patterns. But it is not the case, I am taking interviews, there is not one interview asking same question in next interview. One would go to SQL, Tableau, Analytics, one would prefer Generative AI, one touch all MLOps stuff, another one jumps to data engineering pipelines and stuff. There is no limit for this role and its crushing me to see learning topics growing day by day
I am not data scientist, but I am a data analyst and yes, I regret being in data fields... Initially it was looking exciting but now I am not liking at all...
I'm at comscore
I switched my field from my data science to SDE-backend recently after being Data Scientist for 3 years.
🤧
Took this decision for my long term growth.
More no of opportunities = You can have preference. More negotiation.
Can do remote work
Focus on being good at those 2 areas.
Salary(upper threshold) is no bar if you are skilled enough. Because at some point of time salary saturates then people go for higher studies or different challenging role.
RSU, ESOP is more.
I had not so good experience in the field.
I did most of the thing except data science.
I didn't have much choice related to location, wlb etc.
Data scientist is a role for problem solving. Working for 6 years now, still enjoy learning new things every day, salary is also good. How much $$ are you getting as an SDE? How much experience?
It depends.. if you have few data scientists who are experienced and putting salaries in Ambition box. Average salary is not a good measure here.
I have a mixed role. Essentially i am doing ETL, data analysis, visualization as well as predictive modelling and NLP.
So not a conventional Data Scientist, but I feel with people in this domain, there has to be a constant influx of projects of varying kinds or its easy to lose interest quickly.
I regret being a data scientist as I do not have strong basics in statistics and math. For past 2 yrs I have not been working on any ML algorithm and that has made me forget the basic working of any ML algo as well. I regret not having used my time efficiently.
Yes it has, but almost every domain now in tcs is trying to have its own ds team which could be a roadblock as its in starting phase.
I switched as a data analyst.. but I feel too much to learn. Learnt machine learning, now Learning big data. And cloud is omnipresent with big data now
I believe skills required for SDE is not limited to system design and DS. If you work on java you have be well versed with core api, design patterns, system design, UI technologies like angular or reacts with javascript, devops, cloud etc. companies are expecting all these from a full stack developer. There is very less scope for innovation as you would be fully loaded with work and responsibilities till production.The stack grows every year. Whereas for data scientist or ML ENGINEER, you need to focus on your interest areas and research and code. Here you would exercise your brains a lot.
SDE salary would start from 3lpa. Those who get jobs in MAANG conpanies would are exceptions and posts are rare ans tough. Most of the hiring is done by companies like TCS and infy and over service based who do not offer good package.
There is a difference between full stack dev and backend Engineer.
I think OP is talking about backend Engineering.
There are two types of interview:
1) heavily tech based, project related and all the modules that were used. Live dummy task coding.
2) DSA+system design.
It depends on the company some product based companies ask tech stack related questions more.
While some designs and dsa.
People generally talk about backend or frontend because being a full stack dev requires lot of things.
We have full stack data scientist also.
DS with MLOPS
Equivalent to being full stack dev. (No fixed requirements)
I work as data analyst +data engineer and the job has lately gotten so boring. Doing same stuff everyday is very monotonous. Whereas, I see my friend who is a SDE, he seems to be working on new topics and technologies which looks quite challenging and interesting.
Yes I agree with the above user grass is greener.
People do get bored of doing coding so they do CAT and move to management role. Whenever new tech stack comes you have to study about it in SDE.
If you will consider, interviews are having proper structure. Requirements are well defined in SDE than data field I would have agreed to your points.
So what do you think every SDE gets to work daily on challenging and exciting things? Some of them are also stuck with bug fixing, support, or some other non trivial works. Same goes with QA engineers their work is also redundant. So I think this is a cycle everyone is trying to find their dream job/role.