reddit what does data scientist do on a daily basis - Brave Search

What does a data scientist actually do?

reddit.com › r › cscareerquestions › comments › 1h4jt5m › what_does_a_data_scientist_actually_do

A data scientist’s daily work usually includes cleaning and analyzing data, building models, and turning results into useful insights. Some tasks overlap with AI tools, but most of the job is about finding patterns in data and explaining them clearly, not building complex systems like neural networks or NLP models from scratch. If you want to go deeper into AI or machine learning, starting with the basics is really important. A structured course like this article explains the fundamentals step by step, with hands-on exercises that help build a strong foundation before moving into areas like computer vision or NLP. Answer from jae_amogus on reddit.com

reddit.com › r/datascience › what do data scientists actually do on their day-to-day?

r/datascience on Reddit: What do data scientists actually do on their day-to-day?

April 12, 2019 -

I know they code and use statistical models on huge amounts of data to come to conclusions or train the models even more but what do they ACTUALLY do? What do they spend most of their time doing? What do they rarely do?

I'm thinking of getting a master's at DS but I'm overwhelmed by the amount of tasks "data science" includes and I'm trying to figure out what the day-to-day of a data scientist looks like and how would that interest me.

Drinking coffee, checking reddit and stackoverflow, being in meetings. Joking aside, there is a flaw with your question, and that is that you assume that all data scientists do the same tasks, or have even moderately similar day-to-days. Put differently: you just asked the equivalent of "what do lawyers actually do in their day to day?" I imagine that your day to day looks very different if you're a litigator vs. an IP attorney, vs. an international tax law attorney vs. a forensic attorney vs. a constitutional law attorney. The same is true for data science, but with maybe even looser boundaries. To oversimplify the world, I would say there are going to be 4 types of tasks that data scientists do on some regular cadence: Research: you will have to read up on different ways to solve problems, or different tools/technologies that you can use, or how to tackle specific modeling issues, or how to call a function, etc. It can be as quick as a 5 minute read on a new package in Python, or as long as several weeks to do a comprehensive literature review on modeling methods. Code: once you somewhat know what you have to do, you have do it. Normally you will start by identifying the data that you will need, scoping it, examining it, cleaning it, looking at it some more, do some basic analysis on it, clean it some more, do more advanced analysis, clean it again, put it in a nice format for modeling, more cleaning, and then code up some type of model. Then you clean the data some more, tune your model, debug it, clean, tune, debug, debug debug debug debug debug debug, look at results, they don't make sense, debug debug debug debug debug debug, hey that looks like something that makes sense, oh wait, no, debug debug debug, ok, that looks reasonable. Communicate results: you now have results and you need to convince someone in the organization that those results are good, and that those results are useful. Discuss how to make data science work usable by the organization: once you are able to convince key people that your work is useful, you will need to work with other people across the organization to execute your work in a way that actually drives better outputs. Your usual suspects will be your enterprise development team, a project manager/management team, and the lead business unit responsible for the process that you are working on improving.

Besides modeling, there’s a lot of cleaning, merging, training, parsing, visualization and other prep work for big datasets. Then there’s a lot of admin work, meetings and stuff really eat into my time at work.

reddit.com › r/cscareerquestions › what does a data scientist actually do?

r/cscareerquestions on Reddit: What does a data scientist actually do?

December 2, 2024 -

I’m really curious to understand the day-to-day life of a data scientist. They work with data, but what does that actually look like in practice? Specifically, I’m wondering how much of their work is focused on AI technologies.

Do data scientists work directly with advanced fields like AI, computer vision, natural language processing (NLP), and neural networks? For example, if I want to learn more about these areas, should I pursue a career as a machine learning engineer or is there room for that within the data scientist role as well?

In general: is it a great role to gain AI expertise to maybe found a startup one day or not so much?

They complain how they don't have access to the data that they need, no idea if that data even exists or not, who/what systems produce it, how long it will take to integrate with it, its beneath them to research any of this or assist with tracking any of it down. Once they have the access they need, they spin up poorly configured clusters and run the worst sql queries you have ever seen. All to display a pie chart that en exec looked at once. Then they create a power point showing how they theoretically saved the company a million dollars. Somehow throughout all of this they present themselves as god's gift the the company and the team and somehow leadership believes them.

In practice, they might be querying business data for analytics, retrospection, or creating models for things like forecasting. Their work heavily depends on the engineering culture and the business needs. Could be completely unrelated to ML. DS is I think adjacent to ML/AI though there's a lot of overlap in skills.

reddit.com › r/datascience › data scientist job on a daily basis

r/datascience on Reddit: Data Scientist job on a daily basis

August 13, 2022 -

Hey guys, just trying to understand better some topics that I heard about data science.

I was told that a typical day in a data scientist job was:

1 - Planning (sprint etc)

2 - Data aggregation/manipulation/cleaning/querying

3 - Data Analysis (basicly find patterns in the data and prepare some visualizations of it)

4 - Model Building

5 - Model Implementation

Would you guys add any other specific task? Also, can anyone clarify to me what topics 4 and 5 would be? I imagine it as preparing algorithms to collect more data or calculations for new entries in the database, testing them, etc..

Thanks!

This is missing anything about meeting with stakeholders or efforts to understand their business, needs and concerns. Common mistake for people not yet in the career to omit stakeholders as the #1 priority since school doesn’t teach you about stakeholder management.

A lot of data scientists don't do sprints FYI

reddit.com › r/datascience › what do data scientists do anyway?

r/datascience on Reddit: What do data scientists do anyway?

September 24, 2023 -

I have been working in a data science Consulting startup as a data scientist. All I've done is write sql tables. I've started job hunting. I want to build AI products. What job description would that be? I know this sounds stupid but I don't want to be an analyst anymore

My hot take is that the most valuable data scientists are good analysts first and foremost. You can't "build AI products" or even do machine learning without knowing how to deeply understand your data, and that's what an analyst does. It doesn't mean you should stay in a job that doesn't appeal to you, but don't get sucked into the hype and think that other data scientists are sitting there saving the world with algorithms while you miss out.

What do data scientists do anyway? What the role demands If the task is sql extraction and transformation but the role says data scientist, you're a data scientist It's a marketing term (hyperbole) , if you're hired as a data scientist, you're a data scientist, that's pretty much the crux of it All I've done is write sql tables. Also, I have no clue what this means, do you mean write to?

reddit.com › r/datascience › day to day task of a data scientist / analyst?

r/datascience on Reddit: Day to day task of a data scientist / analyst?

December 17, 2023 -

Hey there! I'm keen to considering switching to a DS/DA role. As part of the process of trying to better understand the role, Would you mind briefly share how you divide your day? Also, mentioning your industry and company size would be really helpful. Bonus: what part do you hate the most :) ?

Something like:

30% Identifying Problems with Stakeholders
20% Data Processing
20% Feature Engineering
10% Model Building
20% Explaining Results to Stakeholders

Looking forward to your insights! :)

50% ChatGPT 50% Waiting for ChatGPT My days are numbered

No, that isn't realistic. At least not for entry-level. You're significantly underestimating the time spent by an entry-level analyst on data cleaning/wrangling and documentation. For entry-level, you almost certainly won't be spending 50% of your time engaging with stakeholders. Entry-level on my team involves a typical weak of 70% deliverables (data cleaning/wrangling, data pulls, descriptive analysis, documentation, modeling under close supervision, strategic communications, etc.), 20% meetings (mostly with the team or other peers), and 10% administrative tasks (e.g., answering emails, weekly prep, etc.). It's pretty unusual for an entry-level to personally present to leadership or other stakeholders.

reddit.com › r/datascience › data scientist day to day

r/datascience on Reddit: Data Scientist day to day

December 5, 2023 -

Hi,

I am new to the field and curious as to what your day to day looks like.

Are you hybrid or remote? Do you have meetings or make presentations?

I have 8 YOE, from what I've seen there are a few different subtypes of data science jobs "analyst" data scientist - pretty much just writes sql queries and does data engineering, doesn't really use "AI" to solve business problems because it isn't necessary "modeler" data scientist - data is usually prepped and ready to rock, they click "train model" and hang out while it trains (my favorite) then monitor and respond to model drift. Might be more devops heavy too "communications" data scientist - they spend about 10% of their time doing actual data science and the other 90% in meetings and making slide decks and presentations I've done all 3 at different companies, some hybrid and some remote - the business determines what type you are. I think the best place to be a data scientist is at tech companies because you're more likely to be a "modeler" due to the advanced engineering culture. Huge banks and legacy companies are usually "communications" with some "analysts" (given the caveat that huge companies can have "modelers" but they usually lag behind in their tech stack and engineering culture). YMMV

Applied data scientist here with 10 yoe in a large tech company. Most of the time I am just making sure data pipelines don't break and migrating from system A to system B. Probably 30% of the time engaging stakeholders to build trust and make sure they don't do stupid shit. 10% of the time managing my boss, his boss, his boss' boss,... ... so they stay grounded in reality and not in a fantasy world where LLM can replace human , and probably 10 % of the time building, modeling, automating stuff.

reddit.com › r/datascience › data scientists, what do you actually do day to day and what models do you use most often?

r/datascience on Reddit: Data scientists, what do you actually do day to day and what models do you use most often?

April 3, 2022 -

Hey pp, just wondering what do you do daily and what models do you use to solve your problems! What is the complexity of such work? I am thinking about switching to a DS role to be more interactive with the data and able to answer questions

I am an ML Engineer (or SWE working in ML domain), whose work is mostly on pipelines and infrastructures and only around 20% is spent on building models. I use big deep reinforcement learning models for my products but I guess it would not be used in DS space due to the black-box nature.

I wonder what would you use most often? How do you interpret and deliver it to others? Any other interesting tasks you do except for predictive modeling? If it is pure data cleaning and regression then I don't know how it differs from BI

Why would you want to be a data scientist if you’re already a MLE? In my experience DS usually pays less. My day to day varies a lot. Kinda depends on the project. I work in a marketing vertical so I build a lot of propensity models. Sometimes I use logistic regression but that’s usually just for stakeholders who force me to. I’ll usually use random forests, xgboost, lightGBM. When I’m doing customer segmentation I’ll use unsupervised algos like Kmeans/hierarchical clustering. I also do forecasting. All of this happens in python but previous jobs required me to use R or SAS. As far as delivering results, that’s also project dependent. For most projects it starts with a proof of concept model that I’ll then pitch to stakeholders. If they like it, I put it into production, meaning it can run on its own (could just be scoring or training and scoring) at a set schedule and populate results into a destination where others can use it. Sometimes that could just be a database table, a marketing tool, and occasionally it’s a dashboard. My company has a big data org so we have people who can build dashboards for us. When I worked in analytics, it was less modeling and more finding insights. I used a lot of Excel whereas in DS I might use Excel a few times a year. Usually just to make charts for PPTs if I think the python plots are too ugly. When I work with analytics people as a data scientist, they’re usually using my model to find insights. All of us use SQL though.

Damn, increasingly def seems ML engineers actually do more sophisticated modeling than DS/statisticians? Idk why you wanna switch lol you are doing more model building than majority of DSs

reddit.com › r/datascience › what do data scientists do on a daily basis in their jobs?

r/datascience on Reddit: What do data scientists do on a daily basis in their jobs?

October 4, 2015 -

As the question implies I am just trying to get a sense of day to day tasks DS have to deal with in their jobs. I am interviewing for some DS positions and I want to understand the daily tasks you do on the job.

^{Background: I work at a boutique data science consulting firm.}

Honestly, it really depends on the project and what stage of the process we're in. In general though, most projects look something like this:

Early phases

Meetings to better understand the nature and scope of the problem, the available data, and the data itself.
Building up project infrastructure
Data ingestion and sanitation

Middle of project

Feature engineering
Target engineering
Preliminary variable selection and correlation analyses
Status update meetings with stakeholders
Back and forth with subject matter experts
Ad hoc analyses
Relaying preliminary insights into data
Building up model training and cross validation infrastructure

Later phases

Building and experimenting with different models
Model selection
Model ensemblification
Upstream debugging
Filling gaps in project documentation
Sanity checking results with subject matter experts
Separating the data ingestion, model training and entity scoring pipelines (if not previously done)
Productionizing the model
Training client in using the product

Meetings. Pulling data. Cleaning data. Meetings. Reading r blogs. A little code, a presentation here and there. Meetings.

reddit.com › r/explainlikeimfive › eli5: what a data scientist does

r/explainlikeimfive on Reddit: ELI5: what a data scientist does

November 21, 2024 - Normally you will start by identifying the data that you will need, scoping it, examining it, cleaning it, looking at it some more, do some basic analysis on it, clean it some more, do more advanced analysis, clean it again, put it in a nice format for modeling, more cleaning, and then code up some type of model.

Find elsewhere

Google Bing Mojeek

reddit.com › r/datascience › data scientists making over 120k usd, what do you do daily?

r/datascience on Reddit: Data Scientists making over 120k USD, what do you do daily?

June 24, 2022 -

Less buzzwords, more technical detail appreciated!

And also any advice on how one can take their career to such heights. Hoping it's not all only down to YOE and location somehow.

Mostly look at memes and listen to lifting podcasts.

Mainly training large language models for text generation, question answering, and different classification problems. I'm either reading research papers tuning hparams for training runs doing engineering work to build out our app testing ways to train models more efficiently the odd data collection job for testing new research Absolutely love my current job. It's purely dev focused. I highly recommend finding a company where data science is core to the product.

reddit.com › r/datascience › what is your day like as a data scientist?

r/datascience on Reddit: What is your day like as a data scientist?

December 8, 2022 -

I’m currently in my first year doing my Bach of Computer Science, I’ve been building personal projects as well but I’m finding I really enjoy using Python to write too and query databases. It’s not for a few years but I’m considering doing Data Science as my major rather than software development but I’d like to here what “a day in the life of” is like in the field

Edit: I’m also drawn to the idea of automation

Let’s just say it’s 11am and I’m still in bed

Every day is different. I work in a team where most of my job is actually making sure other data scientists are doing their job correctly. It's a bit of a weird role, but I actually appreciate the learning that comes with "doing things right". One of the objectives of our team is to serve as an impartial team that's more focused on statistical and analytical rigor (making sure the correct approach is being used to solve the problem, rather than the approach that gives the numbers most palatable to business partners). Some days I'm knee deep in other people's code/writing my own code to do some analysis, some days I work on RnD-esque projects reading papers and thinking about how to implement their techniques in our own custom use cases, some days I'm dealing with bureaucracy of working in a large company just trying to gain access to data. Tbh, I don't work a ton, probs 20h/week at most. It's a pretty chill job but I'm starting to see the number of projects I own growing steadily so this will probably be like 40h in another 6 months is my guess.

reddit.com › r/datascience › jr data scientists- what are your daily tasks?

r/datascience on Reddit: Jr Data Scientists- What are your daily tasks?

October 26, 2021 -

First of all, congrats on landing a job!

I know it varies plenty from company to company, but what are your responsibilities?

cheers

I work in gaming industry. My responsibility is to find bots in our MMORPG games. As our model response to the game server with the bot probability for each user in real-time, we need to meet the criteria of high inference speed and precision/recall.

I am working in consulting as a junior (Data Scientist). My department consults between business and IT and we are always seen as an adapter. I am not in a large DS team, so I have many tasks that go in all directions. In addition, not everything has a direct DS focus.But as u/magicdebugduck mentioned, it's very hard to distinguish between junior and "normal". I actually do the exact same tasks. Seniros tend to have more experience though and are faster as a result, but the tasks aren't really any easier. What I do: - Data Analysis/EDA (Juypter notebook) - Simple ML Algo. for MVPs/PoCs - Programming APIs and linking external APIs / Integration - Dashboards & Reports (Power BI) - Azure Services / APIs - Small automation scripts - Web Crawler & Web Scraping - Chatbot - Process Analysis & Engineering (BPM) - Object Detection with Tensorflow - Requirement engineering & bit data strategy - data quality management

reddit.com › r/analytics › in layman's terms, what do data analysts really do on a day to day basis.

r/analytics on Reddit: In layman's terms, what do data analysts really do on a day to day basis.

February 16, 2025 -

I'm considering data analysis as a career, largely because a) I'm pretty good with spreadsheets. b) I hear it pays well. c) I hear the job market is pretty good.

That said, I know nothing about SQL, Python (or any other programming language). I'm considering going back to school for this. I have a Bachelor's in Operations Management, which has some, but not many, parallel skills. My Bachelor's is also 15 years old and I don't honestly remember a ton of the information.

I'd like to know more about what data analysts actually do, without all the industry jargon. Any insight would be much appreciated.

I create picture books for fancy adults who wear suits. Much like a librarian people come to wanting know things about a subject. I must know enough about the subject to order the knowledge, figure out where to keep it, and be able to find it when it's asked for. It is my job to make sure adults have a great time using my department. That they are rarely overwhelmed or confused. So that part is kinda like customer service. Most of my efforts are spent making people trust me, so I have to spend less time making them trust my work. I also sit through a bazillion standups ( group check-ins) and meetings where we sort sticky notes on a board. ( This is called agile most analyst don't do this) I write code. I tidy warehouses and fill them. But most of all I make picture books for adults and keep them happy and not confused or scared.

If you're starting on ground zero, but have work experience , then look into "business analyst" instead. If you go for data analyst roles, you'll be competing with CS / MIS / IT graduates who are well versed in multiple programming languages since their teen years. Business analyst still need the technical skills like SQL/python/tableau or power bi /R, but they also need to be able to converse with internal teams and stakeholders. My brother is a software engineer and he says it's tough competing with internationals because while it's 'just a job' for him, it's literally 'life or death' for others because not securing a job is a one way ticket back to 3rd world poverty & dead end outlook. From my limited observations in my work setting, companies have no problem hiring the brightest minds for data analyst roles to ensure they're able to produce data. Meanwhile, business analyst have to effectively translate data to non technical stakeholders. I know my whole post is centered around race/origin. Ofc it doesn't apply everywhere and I have native US friends who are data analyst as well. But speaking in generality.

reddit.com › r/datascience › data scientists / analysts, what does your typical work day look like?

r/datascience on Reddit: Data Scientists / Analysts, what does your typical work day look like?

December 11, 2018 -

Hello Data Scientists and Data Analysts!

What does your regular day on the job look like?
What would be an example for a typical project?
What kind of skills are necessary to become a successful Data Scientist?
How important is ML for your workflow?
I’m interested in Data Visualisation. Is this a big part of being a DS or is this more of a Data Analyst Job?

As you can see, I’m a curious newbie with a lot of questions. It would be really great, if you could answer some of them. I’m considering getting my Masters in Data Science, but I’m not 100% sure, if it’s the right choice for me. (Currently working on my BSc in Media Technology and Design). Any advice? (I’m in central Europe btw, if that’s relevant)

"That's not a database. That's a spreadsheet"

reddit.com › r/datascience › data analysts and data scientists, what does your typical day of work consist of?

r/datascience on Reddit: Data Analysts and Data Scientists, what does your typical day of work consist of?

June 30, 2018 -

Please mention your job title and what you do everyday at work. Are you programming? Cleaning data? Running tests? Thinking of how to interpret data? In meetings?

I want to know how you spend your day so aspiring data workers can know what to expect. I recently spoke to graduates from a data science bootcamp and they said they spent most of their time cleaning data while working on their capstone projects. I hate to say this but cleaning data seems incredibly boring and dry, and I just want to know what you do at work so I, and others, can have a realistic idea of what we are working towards.

My job title is Data Scientist. A typical week for me is 40% coding/working on my specific projects. I’m only on one project right now that we estimate will be done in December, and I anticipate being added to another project next month to split my time on. I spend about 20% researching new technologies that we could utilize, 20% data collection / cleaning, 20% fucking around on the internet (jk the last 20% is spent in meetings). I just graduated and began my job a month ago, however I did 2 full time internships at the same company that I now work at so I am pretty comfortable in this workflow. I absolutely LOVE my job. It’s pretty much everything I could’ve dreamed of as a new grad.

There isn't really a typical day. I guess a lot of it is writing SQL queries to get data and there most of the problem is in knowing where the data I need is stored and how as our data isn't that well documented so it takes time to learn where it will be in the format most amenable to your specific use case etc. Other days I can be trying to re-implement the hash function used in the server-side in Python to check some test assignments or using a library to consume events directly from Kafka or writing a custom reducer to look at the historical time series of events a user had. I try to work almost always in Python as then I find it's less of a pain - sometimes working out how to manipulate the data in pandas can be a pain for certain pivot tables or like if you want to plot a grouped, stacked bar chart etc. I think the worst parts are when we have to make stuff in Excel to give to stakeholders or of course the dreaded powerpoint presentations. Some people really hate dashboarding but I made a whole suite of dashboards in Shiny in a previous role (I've moved between various departments) and I liked that work as it was genuinely helpful to a lot of people as opposed to spending ages making some slides that will be breezed over in 30 seconds and might not even make any difference. I've also done some modelling both with anomaly detection in time series and SVMs for text classification. I have studied ML at grad school so I like to get the opportunity to work on it and hopefully it'll be easier soon as we migrate to GCP so deploying models becomes a lot simpler. Generally the job is good - I just really hate making slides and doing stuff in Excel. I'm getting better at avoiding that though :P In general I much prefer working on our python libraries or dashboarding or building models versus doing one-off analyses as I feel the prior work is much more likely to be used multiple times so it feels like a better use of my time.

reddit.com › r/askprogramming › can you explain to me what a data scientist actually does?

r/AskProgramming on Reddit: Can you explain to me what a data scientist actually does?

October 22, 2024 -

What are the languages I need to be specialized in to become one? Which topics should I cover? What's the situation of the job market for junior data scientist? Sorry for asking many questions.

I want to elaborate that the industry is newly trending that a lot of companies actually doesn't understand what data scientist actually does. At the bare minimum, I would just say data scientist is someone who use data to bring value to the business. In the industry, I would expect data scientist should be able to do ML/DL. But other companies are using the terms data scientist to refer data analyst instead, which is technically not wrong but aren't really precise Python, R, Scala are popular in DS field in that order. I would suggest starting with python. Topics are vary, but first you need to understand data. Courses in DA are good at that, You should be able to making/understand graph, manipulate data (aggregation, etc) and getting data from a source (SQL, Excel, etc) Then you could branch out learning ML/DL, or maybe focusing on getting data on various places (table from website, getting data via api)

Data Scientist usually uses Python as their main language and they usually manipulate data and make an analysis out of them. You display data to show what's unique and what can be learn, so in industry you can predict sales trends or you can learn customer behaviour in purchase, or maybe also Product recommendation (which uses AI too), depending on what the industry you do in, it can vary. I hope this helps

reddit.com › r/datascience › data scientist role description- find the bluff!

r/datascience on Reddit: Data Scientist role description- find the bluff!

January 15, 2023 -

Hey guys, do you also get deceived applying for data science jobs that are ACTUALLY data analyst?

I have noticed that if the data science job description includes "BI" and "insights" and lacks "machine learning"- it means that you are being fooled!

What other red flags should I look for to help me filter out data analyst roles disguised as data science?

thanks

Not every data science position has to do with machine learning.

Personally think dashboarding is kinda fun and a welcome break from all the heavy math and modeling. Some relatively brainless(requires you to know the data ofc but other than that) yet satisfying work that people really appreciate.

Also data analytics IS data science, it’s not all about modeling and machine learning. That’s usually a job in a few niche situations and can’t apply in every situation. Being a data scientist is knowing when and where to apply different tactics to get the best result for the time, money, and situation.

reddit.com › r/datascience › data scientists/analysts of reddit, can you eli5 your job?

r/datascience on Reddit: Data scientists/analysts of Reddit, can you ELI5 your job?

March 13, 2018 -

Data scientists and analysts of Reddit: I'm curious about you! I'd simply like to know what you do on a normal working day, what your position really involves (including the stuff that doesn't necessarily appear in job descriptions), as well as clearly understand the difference between these two roles. Thanks in advance!

Do some math
Make some graphs to explain to myself what 1. did
Repeat steps 1-2 until it's worth showing to a co-worker
Repeat steps 1-3 until it's worth showing to a customer
Show to customer
Repeat steps 1-5 until retirement

I'm a data scientist in healthcare and here is what my process usually looks like:

Acquire data
Explore data, usually using some unsupervised ML technique
Analyze, form new hypothesis
Clean data, test hypothesis however I can
If findings are not significant go to 3, else continue
Write report for manager
If no model required go to 1, else continue
Build, train, and deploy model based on findings
Hand off to QA
If bugs found, fix them then go to 9, else continue
Add project to list of things I need to maintain, go to 1

reddit.com › r/datascience › day in the life of a data scientist/analyst (pros, cons)

r/datascience on Reddit: Day in the life of a Data Scientist/Analyst (pros, cons)

June 25, 2016 -

As the title suggests, I would like to hear from any Data Scientists/Analysts about their day to day routine (be specific please) and what you enjoy about your schedule as well as what you find challenging or difficult. I appreciate any input, thank you!

I am an analyst working in a research lab. Here is what my typical day is: 7:50- Get up, check internet, eat cereal 8:30- Catch the bus to work 8:50- Get into work, get settled for the day, start checking e-mails, read a little bit of Reddit for 15 minutes or so if it's not a busy day. If I'm the first one in the office, I'll play music while I start to work until someone else comes in. 9:30- Start working on any projects that I need to finish up. I usually start by doing the easiest thing if there is no priority project because I hate mornings and need to ease in. This could be preparing data files or working on some R/Python code or submitting jobs for analysis. Usually these projects have some sort of deadline 10:30- Eat part of my lunch at my desk because I can't wait until a normal time. 12:00- Most likely have finished up work from the morning. Eat the rest of my lunch at my desk while I'm reading e-mails and take a 5 minute internet break. 12:30- Start working on the harder long-term stuff. This is usually finding and cleaning data files or running summary statistics and making plots, etc. or working on longer scripts. 2:00- Have a project meeting, lab meeting, or conference call. 3:00- Start working on anything that was assigned during the meeting. This is usually modifying whatever I did in the morning. 4:30- Keep working until I get to a starting point or until I've finished up everything I've needed to get done. Post updates/methods from the projects on my online lab notebook. Even though we don't have to stay until 5:00 if we finish everything, I don't like to leave early so I will usually find a paper to read pertaining to something I'm working on. 5:05- Catch the bus home. Cook dinner/eat/think about doing something productive/waste time on the internet/check work e-mail to make sure there is nothing I need to do before tomorrow 12:00- Bed All in all, I really like my job. I work in a pretty laid back office, so I can set my own hours and work from home if I need to one day. Obviously it won't be this way everywhere, especially if you are in industry I would assume. The worst part of my job is if I overestimate or underestimate the amount of time I need to work on a project. Having too much to do is stressful, but I know that I can always take my work home if I need to. Having too little to do is worse. Like today I got everything done in about 4 hours but my boss was on vacation so I couldn't ask for any more work. I don't like to "waste time" at work, so I try to read papers or work on creating an R package or something, but the day really drags for me because it is not as stimulating when I am doing work on a project. A tough project is my favorite and least favorite part. Figuring out how to do something that no one else knows how to do or how to adapt a new software for your needs can be incredibly difficult but is very rewarding when you succeed. Sorry for the ramble, just my $0.02. Take into account that I am quite novice and under-qualified for my position so it may or may not be applicable.

I am an analyst for a marketing team at a startup, here is my day: 6:00am - Wake, Eat/Coffee 7:00am - Gym for my daily workout 8:11am - Bus to work 8:50am - Get into office, start planning the day and lining up my Trello board. I use Trello for prioritization and intake, so keeping it up to date and organized is very important. At this time I also plan what I will say at stand-up, which is where we individually present to the data team what our plan is for the day, what blockers we have, and what we accomplished the day before. 9:30am - Standup. 10:00am - Work until lunch. This is mostly SQL/Excel/Python/R. 12:00pm - Lunch. 1:00-5:00pm - The afternoon is typically filled with work and peppered with meetings. Then I go home. There are LOTS of meetings. As an analyst or data scientist it's my job to validate, to the best of my abilities, the claims that everyone is making. This means having me in lots of meetings, with anyone from interns to the CEO. I have 10X the amount of work on my plate than I have time to do. There are bugs in the data. The problems are hard. None of it's pretty. BUT, it's so fun. So, so fun. The people I work with are incredibly smart, the company is awesome, it's super rewarding, and only god knows why they let me on the team.

reddit.com › r/datascience › what is it like to make a living as a data scientist?

r/datascience on Reddit: What is it like to make a living as a data scientist?

February 28, 2021 -

I'm soon done with my bachelor's in Software Engineering and considering working as a data scientist or getting a master's degree as a data scientist.

My questions:

What do you like about being a data scientist?
What don't you like about being a data scientist?
Does it ever feel like a grind/work?
Did you have another passion you regret not following?

What do you like about being a data scientist? Data. Ever since I can remember I would make data sheets of anything. Data gives perspective that otherwise would be unknown. Ironically, sometimes I like spending 5+ hours just cleaning data because it's so mindless. I would literally just listen to music while on autopilot. What don't you like about being a data scientist? This may be just the company I work for but people LOVE to interrupt me. Does it ever feel like a grind/work? Not really, I love my job. The only time I feel less interested is when I work for uninteresting companies that don't appeal to me. Did you have another passion you regret not following? No. I have many passions but I don't regret it. Data Science is a great path with potential for the future. Even if I were to start a company, Data science is never wasted time.

I've been doing this for the past 9 years at startups, marketing agencies, a 140 year old company with heaps of messy data, and now at the company with the most payment data in the world(think 90-100pb of clean mastered data). at the base of it, most data scientists are hired for business analytical reporting with sql, python, PowerPoint, excel, and tableau/powerbi. Executives use the insights from your work to guide and back their decisions. There's a wide range of use cases both external and internal such as HR data. It pays well but you'll hit a ceiling both in pay and the value you can offer, because to go further it is business domain knowledge and people management skills that are the differentiators. Like most things in tech, be prepared to learn and relearn every few years on new skills and toolsets - sometimes to accomplish the same tasks. Hope this helps, cheers.