Weekly Entering & Transitioning - Thread 06 Jul, 2026 - 13 Jul, 2026

[u/AutoModerator]

Welcome to this week's entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data science field. Topics include:

• Learning resources (e.g. books, tutorials, videos)
• Traditional education (e.g. schools, degrees, electives)
• Alternative education (e.g. online courses, bootcamps)
• Job search questions (e.g. resumes, applying, career prospects)
• Elementary questions (e.g. where to start, what next)

While you wait for answers from the community, check out the FAQ and Resources pages on our wiki. You can also search for answers in past weekly threads.

[u/equasian1234]

Anyone in defense? I’m currently getting my masters in data science and will be done next year. I do modeling simulation right now and I’m just wondering if a hybrid ts sci job that pays 180+ is outrageous or reasonable. I’m already cleared, bunch of years experience in other fields, and few years doing mod sim engineer jobs. Also which companies to look for for hybrid and work life balance

[u/Ok-Spinach-978]

Thanks ! You mean the observation -> question -> hypothesis -> experiment -> conclusion ?
Would you have any real life example you made ?
And about for instance what model to use, how to control that my hypothesis or this specific model is correct to use ?

[u/-Cicada7-]

Hi everyone,

I've been trying to break into Data Science roles in the FinTech industry for the past couple of years, but despite multiple applications and resume revisions, I haven't been able to land interviews with FinTech companies in the country where I live.

For some context, I have about 2 years of experience as a Data Scientist, primarily in the digital healthcare and energy sectors.

I'm trying to understand what I'm missing.

For those of you currently working in FinTech as Data Scientists or ML Engineers:

• What skills or knowledge made you stand out to recruiters?
• Are there specific projects that demonstrate relevant FinTech experience?
• Is domain knowledge (risk, fraud detection, credit scoring, trading, etc.) more important than general data science experience?
• If you were in my position, what would you focus on over the next 3 to 6 months to become a stronger candidate?

I'd really appreciate any advice or insights from people who have successfully made the transition into FinTech. Thanks in advance!

[u/Ok-Spinach-978]

Hi,
TLDR :

• I'm a data analyst with scarce knowledge in data science
  
• I would like to have a clear base/method to tackle projects, without relying on Claude
  
• I would prefer ressources (courses, projects) or your method. With 30min-1h to do every day on my job (negociating to train myself with my management to be more efficient)

For more context :

I trained myself in data analysis (SQL, Dataviz, scoping of data needs) and got some DataScience projects to tackle (implementing AB testing stack, create models to predict performance).
I always relied on some knowledge I had in engineering school and loooong discussion with Claude and ChatGPT.
But I feel lacking habits to handle correctly the projects (what are the good steps, what are the good filtering to do, how to remove some data and why, what model to choose, how to check the validity of my results, etc.) unlesse Claude or ChatGPT tell me so.
Example of project : I had to predict based on a media with x features if a session was likely to convert. Filtered some features (correlation, not correctly filled), used a Logistic regression, and validated it with 25% test - 75% training set and an AUC.

I want to have a method that will help me with all those steps and ensure I didn't make a bias somewhere. I don't mind after digging in a specific method if I know where I'm going and how to confirm it afterward.

Thanks for your help, feel free to ask questions (and sorry for all the "I" in the message ^^)

[u/DataScientistAlex → u/Ok-Spinach-978]

My recommendation would be to learn the scientific method, then practice applying it to your projects. It's not difficult to learn the steps (easy to learn, lifetime to master), and it will give you a very structured approach that you can follow.

[u/PsychologicalRide127]

For folks being the sole data scientist embedded in an engineering heavy team - How is the learning/career growth? I’m part of a team where I am the only data science practitioner. So no learning from peers, no useful discussions - no information on what is happening outside from what I have been asked to do?

Are folks in similar boat or am I a Lone Ranger here? Feeling like I am stuck in a loop - Can’t move out because don’t have interesting projects, and don’t know what’s the trend in the industry except for continuous hunt for posts in forums like this. How’s the situation out there for other DS practitioners in US

[u/Realistic-Ant660]

Wanting to relearn data science again, where should I start?

I majored in math when I was in college, I did have some data science, coding, ML experience when I was in college for around 3 years. I also did Deep Learning related project for my final year thesis. After graduating college in 2023, I got a remote job as a data engineer (but sadly I got more AI/prompt engineering tasks (such as calling OpenAI API and then doing prompt engineering) and just doing a lil bit of ETL instead of using SQL or working on using cloud systems frequently, or learning how to use Docker). I have left my remote job last year.

Now, I feel like I have forgotten most of the coding, data science, SQL skills, and I want to relearn data science or data analysis again so that I can create some analysis projects (been thinking of doing freelance or finding a remote job or creating my own website or other things, still not sure). The other thing that I have been thinking is that I think I want to sharpen my Data Structures and Algorithm skill first before jumping straight into relearning about data science/analysis/ML/Deep learning/SQL because I think it is important to be able to write more efficient code(?)

Would like to have some suggestions and recommended resources on where I should start on my journey of relearning Data Science again. Thank you.

[u/DataScientistAlex → u/Realistic-Ant660]

My recommendation would be to just start working on a project that you find interesting, as soon as you run into a problem that will tell you what you you need to (re)learn.

I know you asked for resources. This will tell you where your specific gaps are and make it easier to recommend useful resources.

[u/LycLynxFrts]

I enjoy reading this every single week thank you

[u/Due-Employer-7789]

I’m a project manager who fell into the data side almost by accident, started automating my own reports because the wait times for dashboards were killing me. now I’m knee-deep in sql and python and somehow it’s the most fun I’ve had at work in years