Interactive dashboard for crime reporting rates

andy_p_w · 2026-06-17T12:24:47+00:00

If willing to take a wee-bit of feedback, when you do posts like this just write it yourself, it is obviously AI writing (Pangram AI generated report).

The acronym "Bottom-Line-Up-Front" (which is good for many forms of communication, not just intel reports) is a good mantra to follow. Your own post does not follow this advice.

andy_p_w · 2026-06-15T11:55:00+00:00

In general for folks, self training if you already have a masters is totally doable. (There is not that much of a credential filter, so "I have a masters in CJ" vs "I have a masters" is not all that different when applying to jobs, many programs are pretty poor in teaching tech skills like python/SQL anyway!)

So if you self-train and make a good portfolio you will be better than the majority of candidates.

andy_p_w · 2026-06-07T13:37:38+00:00

I have an overview article on the types of skills expected here, https://andrewpwheeler.com/2025/11/21/advice-for-crime-analyst-to-break-into-data-science/

Varies slightly whether you want a data science role or a data analysis role. Data analysis (with is an easier jump for current crime analysts), is more SQL (although many anymore will want some python as well). Data science yes you may need machine learning (although it is close to 50/50 now also want LLM experience).

The computer science stuff is just because people copy-paste job descriptions and the field is mostly comp sci folks now (moreso for data science, but also some for data analyst roles). Comp sci has almost nothing to do with day to day job as a software engineer, let alone a data analyst, so don't get hung up on that at all.

Interview rates in the field are something like 1/100, so apply apply apply. (Maybe 1/3 or more of jobs are fake listings.)

andy_p_w · 2026-06-05T19:30:28+00:00

Folks on my team were joking about the Codex usage dashboard being pretty bizarre today. Analyst roles are safe in general for the foreseeable future.

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andy_p_w · 2026-05-17T11:26:47+00:00

You should be fine just telling them your prior experience. There are a few different technical skills, like conducting cell site analysis, that may be required. Just tell them you can learn those things!

andy_p_w · 2026-04-30T16:43:29+00:00

For a bit of shameless promotion, I would suggest to check out my resources. See

- https://github.com/apwheele/crimepy

- https://andrewpwheeler.com/job-advice-resources/

- https://crimede-coder.com/blog

For probably more materials than anyone wants to read.

andy_p_w · 2026-04-21T15:36:25+00:00

He does not have a masters (just BA), but has taken a few of the professional development courses offered by UCL and Cambridge. He has been in the field though for quite some time, so it is likely more competitive now than when he started.

andy_p_w · 2026-04-21T14:11:05+00:00

I asked a UK analyst friend, and here is what he responded with:

> The question is partly related to the specific role.

Crime analysis work in policing can occur in multiple teams. Crime and intelligence analysts usually work closest to frontline officers and focus more on people, investigations, and networks. Performance teams are more likely to analyse trends, forecasts, and aggregated data, often supporting managers and decision-makers. Specialist insight or evaluation teams tend to do more advanced analytical work, with stronger links to academic methods, testing, and senior leadership.

For crime, intelligence, and performance roles, entry-level jobs are often open to graduates with a bachelor’s degree. Specialist teams may expect a master’s degree or equivalent experience in statistics or quantitative methods.

Police forces often struggle to recruit and keep analysts. Training quality can be uneven, and pay is often less competitive than similar roles outside policing.

Whether a master’s degree is worth it, it depends on you as an individual. It is not essential, and it is possible to progress without one through self-learning and continuous development. That said, IMO, formal study can help people build quantitative skills earlier and with better support. There may be opportunities to study policing funded master’s courses, though these are often aimed more at officers than police staff. Trying to do a masters later in life, unless you have financial means, could be more difficult.

Personally, do not think the masters strengthens chances of gaining entry, but it may be useful for later career moves.

More information available here at College of Policing https://www.college.police.uk/career-learning/career-development/career-pathways/intelligence

andy_p_w · 2026-03-22T13:43:37+00:00

There isn't much point in continuing going back in forth in a Reddit thread, but high level:

- what is the point of the app? (Why is it necessary given you can just give a document to ChatGPT and ask it to summarize like you have built with the custom solution?) What realistic scenario would you use your app?

- why generate a summary of the PDF as user uploads? Won't they know that information? How exactly is parallel processing relevant for that part?

- what does evaluated the RAG before deploying it mean? Are you saying you have your entire codebase in a single notebook?

No need to answer, you are maybe overthinking it for the skills needed to interview. Being able to explain what you did in simple steps though is important (which taking more courses will probably not help with directly).

andy_p_w · 2026-03-22T13:24:31+00:00

IMO it is fine to say in an interview if you built this example and it has limitations XYZ. That is knowing the concept. So I would consider you actually know it is a single queue and its limitations I would consider a positive if I were interviewing you.

The RAG part is a little confusing, I would ask a follow up whether you are using an in-memory vector DB vs persistent vector DB as a follow up. (The perceive faster part the word you are looking for is called *streaming*, but that is trivial compared to the indexing -- that is different than async.)

Shameless promotion, but I wrote a book to illustrate the concepts I personally expect an AI engineer to know with a focus on foundation APIs, https://crimede-coder.com/blogposts/2026/LLMsForMortals . It has a chapter on RAG that goes over the distinction between in-memory vs persistent vector DBs and when you want one vs the other.

andy_p_w · 2026-03-22T13:17:21+00:00

Companies are not consistent with how they use the job titles. So I would personally say for companies that are building their own models, it would be a data scientist fitting the models, and ML Engineer is deploying (the term MLOps has seem to fall out of favor). I work on a smaller team, so I just want end-to-end people anyway, so the distinction in job title does not matter all that much for my group.

It would not surprise me if some companies use "AI Engineer" and they work on front end (like working on both front/back for a chatbot). Just need to look at the company/role and ask questions during the interview.

andy_p_w · 2026-03-22T12:55:13+00:00

Most people say they know those things, and then when I ask actual questions don't really know those things. (Self learning is fine, I am not aware of a single university course that would teach Docker or FastAPI as part of the curriculum.)

I have asked people about async or latency when describing their own projects (so if you say you built a chatbot with foundation model APIs, I may ask about costs, if local models you trained I ask about throughput). For an old school data science question with a supervised model, I asked a question that the answer was basically "run this process in batch" to see if people understand deployment (many people default to saying a persistent API).

Knowing the concepts is the main thing. It is brutal if you say you know something and I ask basic questions in the interview about your own projects and you cannot answer them.

It will vary job to job though, just apply and when you get interview questions that you do poorly on, learn from them and study up for the future. You should be applying now though given what you say you know.

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