Monthly Career Advice and Job Openings

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[u/the_immovable]

Transitioning to a career in business analytics from e-commerce (hopefully). How do I think like an analyst in order to prepare for the role? And what's a good CRM to learn?

[u/Lanky_Sir4736 → u/the_immovable]

One thing that has helped me is starting with the actual problem instead of immediately thinking about which tool to use. I usually try to figure out what question needs to be answered, what information would help answer it, and then look at the data. I think your e-commerce background could actually help because you already understand things like customers, sales, and business results. The tools can be learned, but knowing what questions to ask seems like a big part of analytics too.

[u/JAnon106]

I currently make $106k base/$120k total comp as a mid-level data analyst. My job is on-site at a F50 (short commute though). It’s a relatively stable and low-pressure environment, but kind of boring and repetitive. I’ve been looking for something new and especially trying to move into data engineering for the past couple of years.

Recently I received an offer to work as a data analyst at a much smaller, younger company. The job is fully remote and the work seems much more interesting than what I’m doing now. The problem is their initial offer was only $110k base/$122k total comp, and after some back and forth it seems like they’re only willing to come up to $115k/$128k.

I know I’d probably learn a lot in the new role, but it doesn’t seem like enough of a pay increase to justify the risk of switching. Should I take the job and continue applying for data engineering roles? Or just stay at my current job and wait patiently for the right opportunity?

[u/teddythepooh99 → u/JAnon106]

If you're gonna keep applying immediately after accepting the new role, then don't accept it in the first place.

You didn't mention your tech stack, so it's hard to say whether you're competitive enough for DE. I assume the answer is no, since you've been trying to make the switch for "the past couple of years." If you're not learning/applying the necessary competencies on-the-job (or outside work), then take the new job and stick with it for 9-12 months before applying/interviewing elsewhere for DE roles.

[u/JAnon106 → u/teddythepooh99]

At work I mostly use SQL (GBQ) and Python. I’ve built some data pipelines, but the main problem is that my company has a lot of custom internal tools for automation and orchestration that abstract away the underlying tools. I have been able to switch some stuff over to Dataform though (basically dbt for GBQ on GCP).

I’ve also built some data pipelines for personal projects using Postgres, GBQ, Databricks, Airflow, dbt, and various GCP tools (obviously not all in the same project haha). Whenever I build anything, I set up SCM at a minimum, but I do aim for full CI/CD. Meanwhile, I’ve also been working through an online MSCS program, which is part of why my pace of building, applying, and interviewing has been slow.

[u/Temporary_Cherry_414]

We have a data analytics startup and slowly scaling through getting projects from freelance platforms. Need some guidance on further scaling and how to get projects. Is there anyone who can help?

[u/emtaep]

I'm a new-grad with a B.A. in Cellular Biology and Neuroscience, M.S. in Computer Science, and 4+ years of hands-off clinical experience as an ED Medical Scribe, aiming to break into the field of healthcare data analytics/clinical informatics. I was offered a role as a Revenue Analyst in our hospital system's Revenue Cyclic Management team. It's low-paying and doesn't directly correlate with what I aspire to evolve into, so I'm hesitant.

Should I take it in hopes of still branching into my desired field, or would this be a detour?

[u/bowtiedanalyst → u/emtaep]

I would take it. Especially if there are opportunities to use anything beyond excel.

Career progression for me when like Data Analyst 1 - Marketing -> Data Analyst 2 -> Marketing -> Sr. Data Analyst Revenue over three years. If you're good at your job you will be able to shift into a role within the company that's more aligned with your goals (or seek one externally).

[u/ShAZZEY15]

Hi everyone,

I recently finished my bachelor's in Computer Science and Engineering. I learned basic DSA, but my main focus was blockchain and smart contract development. When I tried to find a job in that area, I couldn't land anything, since openings were few and mostly wanted experience.

After that, someone with a non-technical background asked me to support him in a technical role. For a while, I handled the technical work behind the scenes and explained the results and concepts to him in plain language so he could present them in meetings. It taught me how to break down technical problems and communicate them to non-technical people, though I haven't had a formal, titled role yet.

I'm now doing my Master's and learning data science from the beginning. I'd really appreciate guidance on a roadmap that matches what the industry actually expects.

What I'm hoping to learn from you:

1. What's the right order to learn things (Python, SQL, statistics, ML, etc.)?
2. Which tools are essential in real jobs (pandas, scikit-learn, Power BI/Tableau, cloud, Git)?
3. How much math and statistics do I need before moving to ML?
4. What kind of portfolio projects actually impress hiring managers?
5. Should I aim for data analyst first, then move toward data scientist, or go straight for DS/ML roles?
6. Can my CS and blockchain background be an advantage, for example in data engineering or on-chain analytics?
7. Any free or paid resources that you'd recommend?

Where I am now: comfortable with programming basics and DSA, no real experience yet with pandas, SQL, statistics, or ML.

Thanks in advance. Honest advice, including "here's what I wish I'd done differently," is very welcome!

[u/bowtiedanalyst → u/ShAZZEY15]

Visualization (Power BI or Tableau) then SQL, then apply and learn Python.

Just starting to dip my toes into ML/Stats ~3 years into my analytics career. I have used PBI and SQL since the beginning, I started working a lot with python about 6 months in and Pyspark about 2 years in.

Data analyst first, I spent a year trying to get a job in DS before "settling" for a DA job. I do work like, get paid like and have a title like a DS ~3 years in.

[u/ShAZZEY15 → u/bowtiedanalyst]

I am using python for 2 years now, but i learned pandas etc for DA, i was able to solve leetcode medium easily, now im currently on Power BI, and SQL learning them simultaneously, after that ill start applying, then ill shift to DE or DS, where should i apply for beginner level jobs

[u/bowtiedanalyst → u/ShAZZEY15]

I've gotten data related jobs on linkedin. I'm in America though, not sure about elsewhere.

Again, would recommend DA over DE/DS/MLE. Its not 2018, DE/DS/MLE are 2nd analytics jobs, unless you're really, really good.

[u/Tiger88b]

Hello All,

I'm from India - working in India as an analytics manager in a bank. I have 13 years of overall experience.

Wanted your advice on whether I am on the right track or should I try something else?

Background: I have been able to secure only 5 interviews since May 2023 (1 converted but didn't join; rejected in all 4 after that at various stages). In every single case the same story has repeated, even though during the interview everything seems fine, the panel seems satisfied but it never ends in a conversion.

The salary seems to have reached a plateau (INR 50 lakhs fixed + ~7 lakhs in variable & other contributions) where no one is willing to match the current compensation and the job prospects look bleak. Whenever my current firm decides to fire, it will be a nightmare for me to secure a new role.
Most AVP / VP level appointments happen internally so I had few opportunities to begin with. With the current scenario where most firms have frozen external hiring for BA roles (if not actively firing people); I am genuinely concerned about my future to the extent that I have avoided all long term commitments, including buying a home.

My current efforts - I have started learning about building and deploying Agents and Agentic systems. I have consciously decided to stay away from the usual transition into data-science even though I have a decent understanding of the underlying math and have some experience in applying it at work. Even in DS people seem to be facing pressure across organizations with basic modelling being done by automated tools & monitored by juniors.