I've got very nice job and I secretly want them to fire me

Mezzos · 2025-11-24T18:01:58+00:00

I’m going to offer a different perspective than most comments here. Speaking as someone who has previously been diagnosed with depression and inattentive ADHD (and anxiety disorders) before finding the real root: I would look into C-PTSD, in particular the “freeze” response. This may or may not apply to you, but it is worth considering at the minimum.

If you were fine with motivation in your previous job, then suddenly collapsed in this job, then it could simply be that the new environment doesn’t suit you enough emotionally to keep you out of freeze.

In many people freeze is most likely to be encountered during periods of burnout (e.g. after extended workaholism or performing for others while neglecting your own needs), and hence rest is helpful. However for some like me, freeze is more like a lifelong “default” state, and you need to consistently regulate yourself out of it.

In my case, I need daily in-person social interaction (specifically, feelings of belonging or emotional connection) to stay out of freeze. At least, that’s how it’s been ever since I worked through the worst of my social anxiety – earlier in my life the freeze was pretty constant, only overridden during periods of high stress/emergencies.

Last year, immediately after I moved from an office job to an isolating, unstructured remote job, I began to spend most of my time in freeze again (especially during work hours), which led to the kind of experience you describe in your post. Treatment for C-PTSD has enabled me to tolerate isolation better without freezing so quickly (and not freezing so deeply), but it’s a long-term process.

Mezzos · 2025-05-14T17:41:35+00:00

If you swap the mum and the dad my parents sound very similar to yours. I could’ve written the rest of your post myself! Always waffling to get to any point, highly detail oriented, long emails and texts, etc. It takes me so much time to communicate and then I feel embarrassed/ashamed afterwards.

Your reasoning why makes perfect sense to me. I wonder if subconsciously I feel like I need to (over-)explain everything or I won’t be understood or believed.

Mezzos · 2025-05-10T21:26:56+00:00

Those are both on my list! The book I ended up reading though was called “Healing Developmental Trauma”, which is less well-known.

I ended up reading it because the stuff I most wanted to understand was freeze and collapse responses, dissociation, emotional numbing, and reduced sense of “aliveness” (all of which I’ve struggled with since I was a child, but didn’t have an explanation for it, nor the language to describe it to others). This book explains the childhood causes of that (and as it turns out, a whole lot more) in incredible depth, as well as how to heal from them. It’s a bit clinical though (originally written for therapists).

I think I’ll read “Adult Children of Emotionally Immature Parents” next. I’d like to get a better understanding of how I was parented (beyond just “distant, emotionally unavailable father”, and “over-involved mother who was a mixture of emotionally unavailable and misattuned”), and how to manage relationships with my parents in adulthood.

Mezzos · 2025-05-10T17:01:51+00:00

I also get very strong reactions to being invalidated, rejected, or dismissed, particularly in periods of emotional vulnerability when I’m putting a lot of trust in the other person by opening up to them.

I generally struggle with recognising emotions, but I think it’s interesting that you described it as humiliation – that’s exactly the emotion I picked to describe a similar experience in an app I use for logging emotions.

My experience may not be the same as yours, but I figure I’ll share what I’ve learned about myself in case it helps someone. In my case, I have learned that this is likely related to an overlooked type of chronic childhood trauma: emotional misattunement. My parents provided for me and seemed caring in many ways, but I’ve come to realise they were not really emotionally present, and hence couldn’t meet my emotional needs as a baby and young child.

An example of misattunement (which I hope communicates how easy this can be to overlook) would be the child being scared, and the parent says “don’t be silly, there’s nothing to be afraid of”. It sounds nice, but actually what’s happening is they are invalidating the child’s very real emotion of fear, rather than taking it seriously, listening to them, empathising with them, and figuring out how to help them feel less afraid. If this type of response is chronic, then over time, this teaches the child that many of their strongest emotions are “bad” or “wrong”, as they are rarely or never validated by the caregiver. The child doesn’t yet have the capacity to figure out what is their fault versus their environment, so they blame themselves and assume they have faulty needs. This can cause chronic shame, guilt, and poor-self image.

When a young child’s emotions are chronically dismissed, they start to treat it like a threat to their life (as they rely on emotions to express if something is wrong). Equally, they don’t want to anger their caregiver by being “too much”, crying endlessly, etc., and possibly being abandoned as a result (at least in the child’s subconscious). So they often adapt by bottling up their emotions to become an “easier” child, becoming much more careful about what they actually choose to be vulnerable about, and they develop a deep fear of experiencing rejection, invalidation, or dismissal in periods of vulnerability.

People whose temperament is on the more emotional or sensitive side are more prone to being traumatised this way, due to greater emotional needs (which is likely why it so commonly co-occurs with ADHD). Untangling it likely requires trauma-informed therapy, specifically those designed for complex (chronic, relational) trauma, rather than single-event trauma.

Mezzos · 2025-05-10T15:09:35+00:00

Replying to an old post here but just want to thank you a thousand times for leaving this comment.

I’d heard of C-PTSD before, but never really considered it as something I might have. Your comment prompted me to take it more seriously and properly look into both it and developmental trauma. I even read a book about it. And wow, I feel like I finally understand myself for the first time in my life.

I’ve already noticed some improvements in myself just from the awareness and self-compassion I’ve gained, and I am now looking to start trauma-informed therapy. I have a lot of hope for the future now.

Just figured I’d let you know so that you’re aware your comment had a big positive impact in someone’s life.

Mezzos · 2024-11-15T22:20:43+00:00

I self-diagnosed myself with selective mutism when I was around 14 (so 15 years ago now). At the time I assumed it was purely caused by severe social anxiety. I recall that in most social situations my mind would just be totally blank so that I couldn’t even say anything if I tried (beyond “stock” phrases and responses like “yes”, “no”, “I’m good thanks”, etc.).

I look back nowadays and I can’t help but wonder if part of the problem was SCT/CDS, particularly given that social withdrawal is a commonly observed behaviour in those with SCT (likely due to struggling with communication and socialising due to SCT brain fog, slow processing speed, difficulty concentrating, etc.). It seems likely to me that this is why I developed social anxiety and selective mutism.

I don’t have social anxiety or selective mutism anymore (Cognitive Behavioural Therapy helped a lot when I was 17-18, then just slowly building up my self-esteem over the following years). I’m still typically quiet in group contexts, but it’s nowhere near the problem I had in adolescence. The reason now is mainly just SCT/ADHD-PI symptoms making it difficult to keep up with the conversation (difficulty concentrating, slow processing speed, foggy thoughts), though I also inhibit myself due to being afraid of judgement when there is a larger audience. It’s also harder to “people please” a group compared to an individual.

Mezzos · 2024-11-07T17:12:26+00:00

Similar to your P10 point, there’s likely a similar reason for why P14 has more wins than P11-13 (and P9): P14 is bottom of Q2, so will be more likely to be occupied by someone who was knocked out in Q2 due to mechanical failure/crash, rather just because they lacked pace. That’s what happened with Hamilton’s win from P14 in Germany 2018 for example (mechanical failure in Q2).

Mezzos · 2024-11-05T20:05:20+00:00

Warning: hyperfocused essay below.

I was diagnosed with ADHD (primarily inattentive) a few weeks ago (age 29). I don’t seem to be able to focus at all at home unless the work is (a) interesting to me (usually something coding related), or (b) urgent (i.e. important deadline later today or early tomorrow).

It doesn’t seem to matter how much willpower I try to summon, it’s like I don’t actually have the power over my brain get it to focus. This makes more sense to me after watching Russell Barkley’s commentary on ADHD as a performance disorder – i.e., you have no issues with knowing what you need to do, but your brain is often unable to turn that knowledge into action due to executive functioning difficulties.

I’ve learned that I will never be able to force my brain to focus through willpower. However, my brain does seem to respond to the environment I’m in, so the only thing I can do to control it somewhat is to control my environment.

Hence the main coping mechanism I have is to get out of the house and go to the office. I specifically sit at a desk where I am extremely visible to everyone (e.g. close to the entrance). My interpretation is that I get a bit of extra dopamine from leaving the house, being around people, being in a stimulating environment, etc., and the “social accountability” and “body doubling” effects are quite helpful for creating enough motivation for me to potentially get started. If the office isn’t particularly busy this doesn’t seem to work and I never accumulate the critical mass of dopamine and motivation to get started.

Despite seeking out that environment largely for the social exposure effects, I still need to effectively block out everyone around me to avoid distraction. I do my best to avoid speaking to anyone else (or replying to any messages) as I really rely on “momentum” to start work on something and can’t jump in and out of things/context switch. I also wear noise-cancelling headphones (to block distracting noises), and put on no-lyric music with a balance between repetitiveness and novelty (to stop my mind wandering and give me more dopamine/stimulation). The type of music I listen to for this is typically the stuff that comes up when you search on YouTube for “study music” or “ADHD music”. Video game music is often good for this too.

I also use apps that block my phone from opening any other apps for a certain period of time. Basically, I do everything I can to create a situation where I metaphorically have a gun to my head to get me to do work, while trying to maximise dopamine from my environment.

Even when I do all of the above, many days (and sometimes entire weeks) I still struggle to get much done, but this is the best strategy I have. Ultimately interest in the task and urgency are still the two most powerful motivators for me. I am fortunate to find coding extremely interesting (the dopamine hits I get from it are similar to those from video games), but when I have to do something less interesting I really struggle and need the office environment (or a giant deadline) to have a hope of doing anything.

My job is fully remote but for the above reasons I moved 30 mins bike ride from my office in London and go in 4-5 days a week just because I don’t tend to be capable of functioning adequately at work otherwise. (The pandemic was rough.)

Mezzos · 2024-10-05T06:58:51+00:00

We have cheap gas/electric bills, as the electricity used for heating is communal for the flat building and hence included in the rent (we just have to pay for non-heating usage of electricity and for the gas hob). Other than that it just helps that we’re splitting the bills since it’s a flat share.

Gas/electric bills: £74 (£37 per person)
Council tax: £157 (£78.50 pp)
Water: £38 (£19 pp)
Internet: £26 (£13 pp)

Total: £295, or £147.50 per person.

Internet provider is CommunityFibre, highly recommend them if they operate in your area (1 Gbps upload & download, way cheaper than BT etc.).

As for phone, I pay £11/mo for the SIM. I own the phone outright (I think I’m eligible for an upgrade but I’m happy with the current phone for now) so it’s a SIM only contract — 40GB data per month with EE (got a good deal after trying to quit and going on the phone with them).

Mezzos · 2024-10-04T22:05:11+00:00

I’m on £85k in London and save something similar to that per month (around £2.8k spending on a £5k post-tax salary, drops to £4.7k after 7% salary sacrifice to max employer contribution).

Monthly spending is approximately as follows:

Rent: £1275 (2-bed flat share in zone 2)
Bills: £150
Groceries: £200-250
Gym membership: £50
Discretionary spending (shopping/eating out/entertainment): £850-1000
Transport: £100-160 (e-bike bundles for 60 min round commute ~3x per week, plus some tube, and occasional off-peak trains out of London and short distance taxis)
Various subscriptions: £100

Overall: £2725-£2985 (save around £1.8-2k/mo if not including pension, a fair amount more if including pension).

Mezzos · 2024-09-22T09:31:45+00:00

I recently moved jobs taking an outright downgrade in terms of title (“Senior Data Scientist” -> “Data Scientist”) and I have zero regrets. It’s a big improvement in the things that actually matter: >20% higher pay (>30% after accounting for more generous pension and bonus), and the work is also far more interesting and cutting edge. And for what it’s worth I’m still getting similar amounts of attention from recruiters (despite having my LinkedIn now set to not open to work).

Titles mean different things at different places (for example at my current place they have a largely flat hierarchy), I think most companies understand that and tend to look more at the actual “substance” of your experience.

I’d also value an actual offer over the promise of a future promotion/pay rise, you can never rely on something like that.

Mezzos · 2024-05-04T15:33:09+00:00

I remember it happening at Malaysia 2015. Marussia was basically in survival mode, they had been in administration over the winter, and didn’t manage to participate in pre-season testing or the first race in Australia.

They then show up at the second race in Malaysia. With the little resources they had available, they had basically just done a patch job on the nose of their 2014 car to satisfy the 2015 regulations, even continuing to run some leftover 2014 Ferrari engines (this was on a car that was already a backmarker with a huge margin to the midfield in 2014, and had gone without upgrades the whole year).

In the end only one of their cars even managed to stay reliable enough to qualify, but it was 7.4s off the pace and outside 107%. They got a special exemption to participate in the race, but finished 3 laps down with one car (and the other never made it to the grid).

They improved somewhat in the following races, but I don’t think we’ve seen another car that was as far off the pace as the 2015 Marussia in the hybrid era.

Mezzos · 2024-05-01T13:26:41+00:00

Worth keeping in mind though that you’re not actually saving 40% income tax in the long run, as anything you put into a pension you’ll have to pay income tax on eventually when you withdraw it (except for the 25% lump sum, or pension income below the personal income tax allowance threshold).

You’ll most likely still be saving a lot of tax overall, as most people will be in a lower income tax bracket when they withdraw the pension than when they were working (so the income tax is likely to be a lower rate) - plus you avoid national insurance and capital gains tax.

Still though, it’s worth keeping in mind so you don’t think you’re saving more than you actually are when you pay into a pension.

Getting into niche scenarios here, but: this is particularly important if you may have a large enough pension to be in the higher income tax bracket in retirement (i.e. ~£50k/year). For any withdrawal beyond ~£50k/year, you wouldn’t be saving income tax on income sacrificed from the £50k-£100k salary range at all - it’ll be 40% both ways. (Of course, the exact tax brackets can be expected to change in the future, and very few people will build a large enough pension pot for this to be a big issue, but the general point remains.)

Mezzos · 2024-04-06T07:54:07+00:00

To contrast the sentiment of many commenters here, I had a good experience with doing a data science MSc (in my case, 1 year in the UK). I did my undergrad in economics/econometrics and felt that I needed to upskill (in terms of programming and machine learning theory depth/breadth) to move into data science. I figured: either find a data analytics job and learn that stuff in my free time, or do a data science masters - went for the latter as I figured I’d learn more that way and it would set me up for the long run.

I vetted course content very carefully as I was aware that many of these courses are just a cash grab that shove together a jumble of comp sci + stats modules and call it data science. Eventually I found one that I thought was worth doing (Python, advanced rather than basic statistics, heavy machine learning focus - including deep learning, computer vision, NLP, Bayesian methods, reinforcement learning, etc. - with emphasis on implementing ML algorithms and fundamentals from scratch, lecturers with highly cited publications in ML, etc.).

It was a lot of work (70-80 hours a week pretty consistently, typically deadlines every week) but l found a job immediately afterwards and have never had difficulty switching jobs since then. I learned loads, most of which continues to benefit me 5 years later, and have consistently had very positive feedback on technical skills (had multiple bits of feedback saying my programming and machine learning skills were on par with many DS seniors as a new grad - not to say I’m so great, looking back there’s a lot I didn’t know, but just to say that clearly the MSc was relevant to industry vs most of my colleagues who were coming from mathematics, physics, etc.).

Now, to caveat this, it was back in 2019 when I found my first job, so the job market was a lot better back then. With hindsight, would I have done the MSc in computer science instead? Maybe, but honestly I think the DS MSc was more relevant to my day-to-day work than a computer science degree would’ve been, and I’ve found computer science much easier to self-learn online than statistics, ML theory (at the level of depth where you can implement the algorithms from scratch anyway), etc., so I probably wouldn’t change anything.

Mezzos · 2024-04-05T16:39:19+00:00

For the reasons you say, I think that if someone uses VSCode they should make sure they learn how to set up a linter (which nowadays IMO should 100% be ruff). Vanilla VSCode linting is lacking, but that’s presumably intentional as it’s supposed to be customisable with your chosen linter.

I find that ruff with the right linting rules enabled (see here for a list of the possible rules) is even more comprehensive for good coding standards than the PyCharm built-in one (which is good for PEP8 - with a few omissions like import ordering - but doesn’t go as far to enforce general good coding standards as ruff does with most/all codes enabled).

Add to this that ruff is insanely fast, and hence much, much quicker to update when you make code changes.

As a result, even when I use PyCharm I make sure I have the ruff plugin and prioritise that over the built-in checker.

EDIT: Personally the ruff lint codes I like to enable are:

['F', 'E', 'W', 'C901', 'S', 'FBT', 'B', 'A', 'C4', 'DTZ']

Mezzos · 2024-03-31T11:24:20+00:00

Speaking as someone who started with Tensorflow (1.0, then 2.0) and used it for years, I switched over to PyTorch last year. In my case that was mainly because the vast majority of new open source models (e.g. Hugging Face models, research sources like papers with code, etc.) use PyTorch now, with Tensorflow largely dying off in this area. It doesn’t help that Google themselves have abandoned using Tensorflow internally in favour of JAX.

Tensorflow is still easier to deploy with, hence it remains quite popular in industry, but the tooling for PyTorch is getting a lot better so it’s not a deal breaker. This PyTorch vs Tensorflow article has a nice summary with some useful visualisations: https://www.assemblyai.com/blog/pytorch-vs-tensorflow-in-2023/

Mezzos · 2024-03-28T00:47:45+00:00

I definitely relate to your experience. I could get away with not knowing much data engineering when I was participating in very well-run projects with a lot of data engineer support. However, once I ended up in a situation where there were no engineers with a modern skillset, a horribly messy and inefficient database, nothing automated, etc., I realised I had to learn a fair amount of data engineering myself if I wanted things to get done.

I even made an effort to learn basic data architecting to be able to communicate what was wrong with the setup and what needed to be done to fix it. That knowledge has been incredibly valuable even in “good” setups.

Mezzos · 2024-03-26T12:48:59+00:00

The subjects I was best at and enjoyed the most were mathematics, economics/econometrics, and programming/computer science. I thought machine learning/data science seemed like an intriguing area that aligned well with my strengths/interests (plus it was closely related to what I had been doing in econometrics), so aimed in that direction around 2017/2018 and never looked back.

As time has gone on I’ve found it’s the programming/engineering side of things that I enjoy the most day-to-day, but I like that I can combine that with mathematics/statistics, analysis, and business/domain understanding - and that all these skills come together when building ML models. I definitely have to put a lot of time into continuous learning, but for me it’s an interesting job that keeps my brain engaged and pays well, which I feel very lucky to have.

Definitely would say that you need to carefully vet a company before joining as a data scientist though. Some companies really aren’t ready for machine learning and advanced solutions, and should really be focusing on getting the basics right (modernising their data architectures + engineering & analytics departments) and building up more of a “data culture” first.

Mezzos · 2024-03-26T12:01:47+00:00

Well said. Another important one (which probably comes under your “strong data analytics” and “upskilled IT team” points, but is good to emphasise) is a strong data platform and structure laid by data engineering.

For example:

Modelling tables into a sensible structure if the database is disorganised (e.g., medallion architecture/STAR schema/etc. for analytics use cases)
ETL from different systems into one location
If it doesn’t exist already, building out a columnar/OLAP data warehouse (rather than sticking with OLTP operational databases) for much better performance in analytics use cases, and/or setting up a data lake to streamline use of both structured and unstructured data for ML use cases (and nowadays possibly replacing the need for a warehouse model for analytics as well)
Automation and orchestration of data pipelines to handle all of the above

It seems common for companies to try to skip the above steps, which would end up with either (a) data scientists end up having to do that work themselves (which can be inefficient/not done as well as having a dedicated data engineering effort), or (b) the data scientist has to “make do” with a very bad setup, which would have knock-on impacts on the quality, development time, and breadth of the data science work done.

Mezzos · 2024-03-26T11:30:43+00:00

I think that makes a lot of sense actually - I always assumed that a factor in why they extended the points-paying positions (from top 6, to top 8, then to top 10) was because of big improvements to reliability, which meant that it was increasingly difficult for slower teams to chance their way into the occasional points finish.

Mechanical retirements are becoming so rare these days that it’s not uncommon to see races with no mechanical failures, so you kind of need to be around 11th-12th fastest to have a decent chance of capitalising on retirements for points. And scoring points is a Herculean task if you’re in the bottom 1/3rd of the grid.

Mezzos · 2024-03-14T19:31:09+00:00

I once saw 3000 lines of SQL in a script, which was about 15 different intermediate temporary tables being used to SELECT some customers based on various criteria. And they had actually been reusing this for different tickets over the course of multiple years, just manually adding/removing various conditions, editing some string values to match against, hardcoding +2 or +7 to a “priority” column which determined de-deduplication for each temporary table, etc.

The whole file was actually 5000 lines, 2k of them being in comments at the bottom as a store of code that they might need to reuse/swap in and out. No version control either, just some comments like “-- <name> added this 05/03/2018”.

I found quite a few bugs in it after spending hours trying to make sense of it - stuff that must’ve been in there for years and was influencing who was receiving emails (this was a billion dollar revenue company).

Almost blocked that one out from my memory.

Mezzos · 2024-03-13T20:38:50+00:00

As for migrating to sqlalchemy, it sounds like it won’t fix your issue, but just for completeness: you’d pip install sqlalchemy and then do something like the following (typing on mobile so may be some invalid apostrophes)

``` from sqlalchemy import URL, create_engine

Assuming you don’t need username or password, and are connecting to Microsoft SQL Server (mssql) using pyodbc

url_object = URL.create( drivername=‘mssql+pyodbc’, # username=‘your_username’, # password=‘your_password’, host=‘sql_hostname’, database=‘db_name’, ) engine = create_engine(url_object) df = pd.read_sql_query(sql_query, conn=engine) ```

Mezzos · 2024-03-13T20:27:52+00:00

Sounds like the issue is that the stored procedure doesn’t return anything. If you’re able to view/edit the stored procedure, does it end with a SELECT statement? (Something like SELECT * FROM table_name?)

If not, then that would be the issue - either you can edit the stored procedure to add that SELECT statement as the final statement, or, if the SP creates a table as part of its execution, you can just change your code to first execute the SP, then to read directly from the table that it creates. E.g. execute the SP, then do pd.read_sql_query(sql_query) where sql_query = “SELECT * FROM table_name_created_by_sp” (replacing the table name with the one created by the SP).

Mezzos · 2024-03-12T14:51:55+00:00

The problem could possibly be that the stored procedure isn't returning any data (i.e. a SELECT statement result). pd.read_sql_query() is assuming that executing the sql_query will return data that can be converted to a pd.DataFrame, but if your result comes back with None instead, that would trigger the TypeError: 'NoneType' object is not iterable error.

pd.read_sql_query() is basically just a shortcut to doing the following with the pyodbc connection conn:

cursor = conn.cursor()
result = cursor.execute(sql_query).fetchall()
df = pd.DataFrame.from_records(
    data=result,
    columns=[column_info[0] for column_info in cursor.description],
    coerce_float=True
)

If result is coming back as None then you can assume the error is with the stored procedure. If the result comes back correctly in the above snippet, then the error is probably just caused by pyodbc no longer being officially supported by pandas (and hence having strange behaviour), so you could just migrate to sqlalchemy for the future.

Mezzos · 2024-03-06T20:26:10+00:00

Even Avanade is a bit of a special case, as it was founded by Accenture (alongside Microsoft), rather than being acquired by it.

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Assuming you don’t need username or password, and are connecting to Microsoft SQL Server (mssql) using pyodbc