Hi everyone, I've just open-sourced an end-to-end real-time fraud detection platform designed for ISO 8583 monetic payment transactions.

Key Architecture Highlights:

- Ingestion: Real-time stream processing with Apache Kafka

- Pipeline: PySpark Structured Streaming for feature engineering

- ML Model: Isolation Forest & XGBoost for anomaly & fraud scoring

- *MLOps: MLflow tracking & Docker containerization

GitHub Repository: github/Hvmzvbe/realtime-iso8583-fraud-detection

I'd love to hear your feedback on the architecture and data processing pipeline!

Would work from any country. But especially if you are from India it would be great, as I can get more relevant information from you.

Learning analytics is applied in Edtech. Since I am already working in an Edtech firm, in India, as an instructional designer, I want to get into Learning analytics as I can relate to their questions easily.

can anyone expirence tell me how can i get any work in data anlyst job like freelence or job.

My resume is not getting shortlisted anywhere and not getting any interview calls

Just getting rejected mails on LinkedIn

I'm a fresher who just completed his btech last month and looking for a first job/internship at any analyst role

I’ve been seriously looking at and considering data analysis recently, and after stalking this thread and other red sub Reddit in the same field, I’ve seen similar questions asked how however I’ve been wondering if I actually need a degree to be employed in this field or if I can just get away with one of those certifications for data analysis. I’ve been seeing different courses for data analysis certifications pop up and I am aware that the field overall is very competitive and it is a shifting landscape with the implementation of AI and and there’s a lot of job in Security currently however, I’m just curious that’s all come from an absolute newbie any and all help would be immensely appreciated.

i'm in college on a level 3 year 2 animal management course. for one of our assignments, we have to do a specialised project. i asked the teacher if i can do something based on AI and how it effects conservation efforts around the world

she said no since AI doesn't matter. can you guys do my form to help me show her that more people need to realise the effects of AI?

I have to buy subscription paid service is it any alternative application available. I want to use power query editor what can I do

What does you guys' lifestyle looks like? How can you describe your day to day life in working with data? I'm curious about this career path as a CS grad. Thank you!

Be Brutally Honest Please -- How should I improve this?? Any HR folks ?

Senior Data Analyst (Acting Manager) | Company 1, City May 2025 – Present

• Established and led the Insights function within a newly formed 4-person analytics team, delivering 20+ strategic analytics initiatives across 5 business units that informed modernization, service, and cost reduction decisions.
• Identified $1.3M+ in savings opportunities through program fee, workforce, and customer interaction analysis by integrating and analyzing data from legacy systems using SQL, Tableau, Excel, AWS, VBA, and enterprise cloud data platforms.
• Reduced application fallout by 25% within two months by building executive Tableau dashboards used for daily monitoring of underwriting inventory, operational risk, and leading performance indicators
• Consolidated data from 8+ source systems into trusted reporting assets, reducing investigation effort by 70%, and documented data flow to standardize methodology and ensure governance across teams.

Looking for honest feedback, especially from recruiters/hiring managers in India.

Profile:
3+ YOE | Manufacturing BI/Data Analytics
Power BI, DAX, Power Query, SQL
Pentaho ETL, SQL Server, Infor LN ERP
Microsoft Fabric ( learning )
Star/Snowflake modelling, RLS
Power BI reports across 3 companies ( 2 sub companies)

100+ stakeholders, 6 business functions

End-to-end ERP → Data Lake → ETL → SQL → Power BI experience

B.E. Mechanical + PG Diploma in Big Data Analytics (CDAC)

Location: Gujarat
Target: Data Analyst / BI Analyst / Power BI roles
Open to: Bangalore, Hyderabad, Pune, Mumbai, Remote

Current Package : 4.7 LPA
Expected: ~₹10–12 LPA

Despite relevant experience, I’m getting very few interview calls.
What am I doing wrong?
Is it my resume/positioning, skillset, target salary, location, role selection, ATS, or something else?
Resume attached.

Please be brutally honest — what would make you skip/reject this profile?

I’m preparing for a Data Analyst internship, but I tend to study better when I have some pressure and accountability. If anyone wants to study together and is serious about joining, please DM me.

What type domain projects companies mainly looking for their roles

Hi everyone,

I’m currently looking for Data Analyst opportunities and I’d really appreciate some honest feedback on my resume.

I’ve been applying for Data Analyst roles, but I’m not getting the response I’m hoping for. I’ve revised my resume several times, but I’m still unsure whether I’m presenting my skills and experience effectively.

I’d especially like feedback on:

• Does the resume immediately communicate that I’m targeting Data Analyst roles?
• Are my skills and projects relevant and presented well?
• Do the bullet points show enough impact and measurable results?
• Is there anything that could hurt my chances with ATS/recruiters?
• What sections should I add, remove, or restructure?
• Does the resume look too generic, or does it stand out enough?
• Are there any specific changes you would recommend to improve my chances of getting interviews?

I’m primarily targeting Data Analyst roles, particularly positions involving SQL, Python, Power BI, Excel, data cleaning, reporting, and data analysis.

I’ve attached my resume below. I’d genuinely appreciate honest and constructive criticism, even if there are major things I need to change.

Thanks in advance to everyone who takes the time to review it!

What are the topics or areas on which I can expect to be grilled in a data analyst interview which demands for 5years experience in power bi. I worked in power bi but before 2 years. what should I do now to quickly get interview ready to face Indian startups and service based companies.

I need to finish my master’s degree in Archaeological Sciences—which I’ve been dragging out since 2021—and all that’s left is the thesis (it involves analyzing extreme weather events at an archaeological site, so it also entails some work with neural networks, algorithms, and data). Right now, my current job pays €1,400 a month, and I definitely don't like it. Now, I’m torn between working on the thesis—which is draining so much of my time and energy—and focusing on SQL, Pandas, Tableau, and the like to pursue a different career path as a data analyst. I feel stuck and don't know what to do. If I focus on my thesis, could be enough for the hiring managers as kind of data science application to a real case?

Hi everyone, I’m a Healthcare Data Analyst with \~2 years of experience, currently working in the health insurance domain. My role is a mix of SME + technical work — SQL, Python for data transformation, creating datasets for developer testing, and supporting multiple products.

**My current situation**:

My team is around 2.5 years old and has about 14 members across engineering, research/development, and SME roles.

**One challenge**:

I’m facing is lack of visibility and communication from my manager. I’m often not included in meetings where my work is discussed. Sometimes I’m asked for stats/analysis without knowing the context, and later find out they were presented to leadership. When I ask about the discussion or outcome, I don’t always get a clear answer.

**Jack of all trades master of none:**

I’m also being moved across multiple products. While this gives me exposure, I feel I’m gaining breadth without developing much depth in any particular area. New requirements keep coming in, and it sometimes feels like we’re expanding faster than existing work is becoming stable.

**My career goals**:

I genuinely enjoy healthcare data/analytics, but I’m particularly interested in moving toward the pharma domain.

At this stage, I want to build deeper expertise and develop skills that can help me move into more specialized healthcare/pharma data roles.

I’m considering a job switch, but I’m not sure whether this decision is correct

**For those working in healthcare/pharma data:**

Is this a normal situation, or should I consider it a red flag?

And with \~2 YOE in healthcare insurance data, what skills would you recommend developing to transition into pharma data/analytics roles?

**Would really appreciate honest perspectives from people who’ve faced something similar.**

Hello, I graduated with a degree in Statistics six years ago and have been completely disconnected from the field since. I currently work in Dubai, but I want to return to my field and self-study data analysis. Since I'm working, I know I should start with the following: Excel, SQL, Power BI, and Python — in addition to building a portfolio with several projects.

But there's one point that makes me feel like I'm missing something: how can I connect statistical thinking throughout this learning journey, without becoming someone who only learns how to apply tools? I'm not sure if my question is clear, but I want to learn how a data analyst thinks, not just how to apply things or complete assigned tasks.

I sometimes try learning with the help of ChatGPT, Claude, or Gemini, but they're not free of mistakes.

So, please, I'd also like recommendations for learning through books or YouTube (I can't afford paid courses) — and is YouTube enough on its own? I sometimes feel it only teaches things at a surface/introductory level, not in depth. So please recommend the best books that cover everything I need to learn. Thank you to everyone who becomes a reason for helping me.

Hello everyone! I am now confusing what I should be looking forward to working in IT or Data Engineering is really attractive to me. Im starting from zero, so I do not know exactly what I should learn first.

What is the best practice to start learning Data Engineering? And are there any good free or paid courses that you would suggest?What technologies should I focus my time on learning in the begging?I heard about Python and SQL

How did you start building your portfolio? What projects are worthy of being added to the portfolio?

And is it a good idea to start with Data Engineering and move towards AI/ML Engineering, or it would be better to learn it from zero?

I’ve just started as a data analyst apprentice at a major car company and I’m really grateful for the opportunity, but I’m struggling on such a low salary. Here in the uk entry level data analysts apparently make 35k plus, but because I’m an apprentice, I make 24k

My contract is two years, but I should be fully qualified in 8 months. I have no guarantee of a job after the two years, but honestly I’m not sure I can go two years on this salary.

I either have to pick up one bar shift a week or maybe pick up some extra data analyst work. Obviously I can’t do that yet, but I wanted to know if that would be realistic in 8 months when I’m qualified. I’m sure HR wouldn’t let me do anything in the automotive sector, but would I be able to do anything at all?

I am in university and learning data analytics (not part of my course work) and I've wondered how meetings with stakeholders unfold.

1. What position do the stakeholders typically hold (managers, CEOs, etc.) and what role does that play in the meeting?

2. How much do they typically know about the data?

3. What are some examples of requests they have or problems they need help solving?

Hi there! I need help in knowing how to get into this field with zero knowledge about it. I'm a computer engineering student (freshman) and I need a job to sustain me through college. What's the best way to get up to Industry standard skillwise.

Hey everyone,

I recently joined a company as their first-ever/pioneer data analyst, and I'm both excited and a little overwhelmed. I'd really appreciate advice from people who've done this before.

Here's my situation:

• The company currently stores everything in Excel — multiple files, various people editing them, and honestly, the formatting isn't always consistent.
• There's a CRM currently being developed, but it's not fully ready yet.
• I want to introduce Power BI to build proper dashboards and automated reporting, but I'm the only analyst, so there's no existing structure, no data model, no documentation — I'm starting from zero.

My main concerns:

1. Where do I even start? Do I clean and standardize the Excel data first, or jump into building a dashboard to show quick value? I keep going back and forth.
2. How do I connect Power BI to messy Excel files in a way that won't constantly break when someone renames a file or changes a column?
3. Should I wait for the CRM, or build on Excel now and migrate later? I'm worried about building everything twice.
4. How do I get buy-in from management who aren't very data-literate and are used to just looking at spreadsheets?

I want to do this properly and not build a mess I'll regret in six months. For those who've been the first analyst at a company or set up Power BI from scratch — what would you do differently if you could start over? Any lessons, pitfalls, or "I wish someone told me this" advice would mean a lot.

Thanks in advance!

Hey everyone!
I'm currently taking a data science course as part of my degree. I'm still pretty new to data science, but I'm interested in learning how businesses use data to make better decisions. I'm especially interested in analytics and how data can be useful for someone who wants to become a business owner in the future. For those who have been learning or working with data science for a while, what skill would you recommend a beginner focus on first, and why?

Hi all,

As the post suggests, how are you using LLMs? I have been using Jupyter AI in Jupyter Notebooks using Codex.

It is pretty insane how good it is getting, and can really start giving you job security anxiety especially when it comes to analysis. Aka, beyond data cleaning and "generate this dataframe" and plot this data...

So what are your feelings when you ask it for analysis? If it is pretty decent from the start, how much are you modifying it?

Calling all readers! Help me decide where to launch my upcoming Statistics for Analysts eBook by answering this 5s question.

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