Should You Join a Big Corporation or a Small Startup As a Data Scientist?
How do you know which one is for you and what to expect from each
How do you know which one is for you and what to expect from each
It’s the end of the year! That means it’s the holiday season, it’s the bonus and promotion season; it is also the time a lot of people are looking to make a job switch. No matter if you are looking for your first job ever, or the tenth switch in your career, you will always wonder what kind of company you want to work for. I personally went through phases of different preferences when it comes to this. The old me only wanted to work for the companies that most people around the world know; however, after working for several big companies, I’m obsessed with the startup world now. Who knows whether I will change my mind again a few years down the road, but what I DO know after working for both big and small companies is the differences between them, so the next time I want to make a change, I’m better informed and better versed in my decision criteria.
In case you are looking for your next gig and are having a hard time deciding the type of company you want to work for, I’m hoping to share some of my learnings from working in both worlds and help make your decision a little easier.
It’s not about the money (or is it?)
We all join companies for the mission, for the ultimate goal of changing the world, right? But let’s not sugarcoat things, compensation is a big determining factor. It shouldn’t be a surprise for most people that bigger companies, in general, have more budget than smaller companies when it comes to hiring. I say “in general” because it’s definitely NOT 100% of the case.
There are good websites where you can compare different companies’ compensation packages such as levels, indeed and more. But don’t just focus on the total package, it’s also important to notice the cash-bonus-equity breakdown. Typically, you can expect startups to offer lower base salaries and a larger share of the total compensation in the form of equity; as a result, accepting a startup offer means higher risk (since the startup might fail and your equity becomes worthless), but potentially high returns (if the company exits at a high valuation). In addition to the volatility of startup equity, keep in mind that it might be years until you can actually sell it, whereas you can usually sell your equity in a large public company soon after you vest it.
If you consider joining a startup, more so than with a large company, you should believe in the startup’s mission and product offering; your job security and compensation are directly tied to its success.
You are staying for the long run (or are you?)
Let’s face it, nobody can be sure they will be in the same company until they retire (on the contrary, most people can be sure of the opposite). So it’s important to think about the long term and your potential exit strategy when you decide to join a company.
In general, bigger, more famous companies serve as a stamp of approval in recruiters’ eyes. That means you will get more outreach from recruiters on LinkedIn and other platforms once you have joined a brand-name company.
But the importance of this stamp of approval really depends on your current resume and where you have already worked at. Accumulating brand names has a decreasing marginal benefit — if you already have one or two recognizable brands on your resume, your next move is almost irrelevant.
But if you are a new grad or have only worked at small startups in the past, having a big name on your resume will definitely help you attract more attention from recruiters for your next move. If you are making a career transition, either from one industry to another or from a different field into data science, having a brand-name employer would also help. Let’s say you are moving from finance to data science in the tech industry; being a quantitative analyst at Goldman Sachs will get you more response than being a quant at a small boutique bank that tech recruiters won’t be familiar with.
Company culture
Company culture is a big consideration for me, as a bad culture will ruin not only morale but also productivity.
One of the biggest deal breakers for me in terms of culture is office politics. I’m fully aware that whenever there’s people, there’s politics, and it’s unavoidable. But since politics slows down companies’ progress by creating many types of my least favorite people — the empire builders, the power gatherers and the credit stealers— I would like to avoid it as much as I can.
There is usually more politics in bigger companies that already went through the growing pain and reached a steady state, simply because people have the time for it. In smaller startups, people are too busy hustling to waste time on politics.
There is also less hierarchy in smaller companies because.. well.. you simply don’t have enough people for that. How can you build a 10-layer org structure with 11 people?
The flip side of hierarchy is structure. You can usually expect to find better-defined scope and clearer team mandates and swim lanes in bigger companies that have been developing for a lot longer. If you are uncomfortable with ambiguity, startups might not be for your; while some people (me included) find it liberating to have the autonomy to get things done, the lack of clear guidance and established processes can be intimidating to others.
Although there is a strong correlation between company size and the amount of what I find to be “bad culture”, there are definitely outliers. So it’s important to try to find out as much about a company’s culture as possible before you commit to the choice; remember, interviews are a two-way street and you should use them to get to know the team.
Growth and impact
Based on past experience, I find there are more opportunities for growth in smaller companies. This abundance of space for growth can be attributed to several factors.
The lack of structure and hierarchy in smaller companies means there is more room to take initiative, no matter your tenure. It’s also easier to take on more responsibilities and get more exposure.
Companies that are going through growing pains are usually strapped for resources, everyone needs to wear multiple hats and take on tasks that don’t fall within their immediate responsibilities. Instead of being a data scientist, you usually need to be a combination of data engineer, data scientist and data analyst, or maybe even data product manager.
Compared to mature companies, smaller companies usually don’t have frameworks and playbooks for everything readily developed. As a consequence, you will have the chance to take novel approaches for problems you encounter.
With that being said, more mature companies have often developed a lot of best practices you can learn as an early-tenured employee; not to mention you simply have more people to learn from in bigger companies.
Lastly, because there are more chances to take on big projects and responsibilities in smaller companies and there are typically fewer people involved, it’s easier to visualize your impact and feel a sense of impact whereas in bigger companies it’s easier to feel like a small cog in the giant wheel of the corporate.
Work-life balance
A well-known phenomenon is that most startups have a hustle culture. Startups are fighting for market share or even survival, and people are usually very results-driven and won’t shy away from working on weekends and overtime if that’s what takes to get things done. This is also partially due to the fact that there are less clear swim lanes and lines between teams are blurred, so it’s easier to take on more responsibility if you want to.
More established companies, on the contrary, have had longer time to figure out role clarity and scope, and their business is in more of a steady state; so it’s easier to plan the work to adhere to normal working hours. Bigger companies also usually have more headcount to share the workload; so the work-life balance is usually better in bigger corporates when compare to smaller startups.
Key takeaways
There are lot of different factors to consider when deciding what kind of companies to work for. It’s definitely helpful to know the generic comparison, but you should always try to learn as much as possible about the specific company you’re considering in order to make better judgements since there ARE outliers to the general trend.
You also might want different things at a different stage of your career, so it’s not uncommon for people to switch between different types of companies; don’t be afraid of making the wrong choice, you can always try things out and make the switch when it’s not working out.
Want to read more about data science? You might be interested in these articles:
Signs You Are Using Data Visualization Tools Wrong
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Avoid These Five Behaviors That Make You Look Like A Data Novice
And be a trustworthy, likable data partnermedium.com
5 Mistakes I Wish I Had Avoided in My Data Science Career
I learned these lessons the hard way so you don’t have totowardsdatascience.com