The Best Data Science Software Development Companies in 2023
for Software Development Outsourcing
Because data science is an amalgamation of so many disciplines and because the term itself is unspecific, it can be hard to pinpoint how businesses can benefit from data science services. But, as the best data science companies are in such high demand, they must provide significant value.
In fact, data science has many practical applications. Logistics companies use it to optimize routes. The finance industry uses it to reduce fraud. E-commerce stores use it to improve conversions. Bankers use it to find patterns and make forecasts. The agriculture industry uses it to identify diseases and improve yields.
Even some governments are considering using data science to implement policies. In short, the applications are limitless. Any process where making decisions is based on insights gathered from a large corpus of data is founded on data science.
Consequently, it should come as no surprise that the US Bureau of Labour Statistics predicted that the average growth rate between 2021 and 2031 for data scientist jobs will be 36% (the average for other jobs is 5%).
Similarly, the data science market was valued at $95.31 billion in 2021 by Polis Market Research and is expected to grow to 695 billion by 2030, with a compound annual growth rate of 27.6%. So, the industry is definitely expanding as more and more businesses realize the importance of data science to their routine operations.
But here’s the problem – there is a shortage of qualified data scientists. It’s simple supply and demand. The demand for data science services is skyrocketing, but there aren’t enough data scientists. Which makes it difficult to find a data science vendor to work on your project.
One practical solution is to utilize the global talent pool by outsourcing data science projects. And that’s what we’re here to help with. Below, you will find a list of the 16 top data science companies in 2023. So check out the list and find a company that offers the services you need.
How Does The GSC Ranking Algorithm Works
We conduct an in-depth investigation into the available software development companies operating within a given region. This helps us gather an exhaustive list of potential companies to evaluate.
Utilizing a combination of third-party tools, online resources, and client feedback, we apply our proprietary algorithm to screen the software development companies and select the most capable and trustworthy ones in each country.
Our ranking algorithm determines the top 15 software development companies based on experience, expertise, reputation, and customer feedback. Only the top-ranked companies are presented to guarantee the best options for clients.
Best Data Science Software Companies in 2023
1Thoughtworks
2IFS
3DXC
4Altamira
5Ateliware
6KMS Solutions
7Josh Software
8Poatek
9UDS Tecnologia
10eTeam
11GENESYS
12ACID Labs
13Hatch Works
14Virtido
15ITERON
163XM Group
What Is Data Science?
In the simplest of terms, data science is a multidisciplinary field that studies data to extract valuable insights. Data science utilizes mathematics, statistics, data analysis, and various branches of IT to solve problems. In practice, it structures unstructured data, often with the purpose of creating advanced algorithms to be used by businesses.
How To Choose the Best Data Science Vendor in 5 Steps
Outsourcing a data science project is no small task and it shouldn’t be taken lightly. Here, we will discuss the steps you can take to find the best data science company that can help you complete your project and provide the services you need.
Preliminary Step – Understand Your Needs
Data science is a very expansive field with a lot of subfields. Many companies that work with big data often believe that outsourcing data science projects is the solution to all of their problems. However, while data science often is the solution, you don’t necessarily require more complex services. Here are some common services provided by data science companies:
- Data extraction/retrieval
- Data annotation
- Data analysis
To exemplify, let’s say you run a large e-Commerce shop for tech. You want to position yourself as an authority in the field and decide to write a report that will delve into the behaviors of customers in 2023. You want to know which types of products are popular in 2023 compared to 2022.
While this might seem like you need advanced data analysis services, you likely only need data extraction. Now, if you wish to find out why customers are buying certain products, potentially to predict which products will sell in the future, you would likely need statistical analysis services, which is a subset of data analysis.
Now let’s talk about data annotation and machine learning. It’s good practice (in truth, almost obligatory at this point) to categorize and classify products on your website so that customers can easily browse it. This is done through data annotation.
If you want to go a step further and have your website recommend products to your customers that they might be interested in based on their previous searches, you would need data annotation, extraction, and to train a machine learning algorithm.
All of this is a long-winded way of saying that you should understand your needs in depth before you start searching for a data science vendor. With that out of the way, let’s talk about how you can find the best data science companies for your project.
1. Reputation and References
The first step is to create a longlist of data science companies you may hire. There are many independent review platforms that can help you with this. So browse data science companies, and look at their ratings, reviews, and customer comments.
As a side note, most companies will have positive customer feedback on their website or social media. It’s normal to want to present yourself in the best light possible, is it not? But that doesn’t give you the full picture, which is why we recommend you utilize independent review platforms.
Similarly, if a person or business partner you trust refers you to a company, they are probably worth including on your longlist. Now, filtering companies in this manner is necessary, but it’s also tedious. Which is why we did it for you. All companies on our list of the top data science companies are worth going on your longlist.
2. Specific Expertise and Demonstrable Experience
Once you have your longlist ready, it’s time to start narrowing it down. In the world of data science, nothing beats demonstrable experience. So try to find out which projects a company has successfully completed. Search for their portfolios or case studies to see what they can accomplish and how it compares to the needs of your projects.
Additionally, look at what certificates the company has or what training their staff is provided. Again, data science is a very expansive field and you want specialists that are a good fit for your project, which typically means very specific training.
3. Evaluation of Individual Companies
By now, you should have:
- clearly defined your problem
- selected companies by reputation
- found data science companies that have the necessary expertise
So it’s time to evaluate each potential vendor. The first step is problem exploration. Approach companies with your problem and provide them with operational data. It is up to them to examine whether your problem can truly be solved with data science.
The best data science companies will first verify your data and your needs before proposing a scope of work. If you need more advanced services, like business analytics or the development of machine learning algorithms, the company should first crate models and provide you with preliminary results.
And this process can take several months. Only once both you and your vendor are satisfied with the accuracy of the solution should the real work begin.
4. Return on Investment
Just because a solution to your problem exists doesn’t mean it’s worth implementing. Your investment needs to pay off, potentially within a set time frame. So the company you wish to hire should calculate the costs of the projects and then you can jointly calculate the return on investment.
5. The Location of Your Vendor
Data science is in high demand and it may be difficult to find local vendors that can do the job you need. This is why it is worth looking into outsourcing your project to nearshore or offshore companies.
Data science companies from outsourcing destinations can have the same level of expertise as local companies, but outsourcing to other countries comes with its own set of challenges. It is a viable option, and often the only option, but you should weigh the pros and cons before committing to outsourcing data science projects to offshore companies.
Don’t Rush It
Quality data science services take time. Outsourcing a data science project is much like partnering with any other company. And when you are looking for a partner, you do due your due diligence and vet them appropriately. The same applies here. Contact different companies, see what solutions they offer, and how their goals align with yours.
We hope this list of the 16 best data science companies has helped you in your search. If you also need other services, like AI, custom software development, or product design, we have similar lists that can help you along. So take your time and find a company to partner with.
Frequently Asked Question
The cost of hiring a software development company largely depends on the company’s quality, technology and reputation. Nevertheless, they tend to range between $40 and $100 USD per hour.
Software development outsourcing is contracting an outside company to assist in the development of software or completely taking over the development process.
Outsourcing software development has the following primary benefits:
- Lower costs;
- Access to a larger pool of skilled developers;
- Speedy execution of software projects.
Software development outsourcing is typically done in 6 stages:
- Defining the scope and requirements of a project;
- Finding an outsourcing partner;
- Selecting the most appropriate outsourcing model;
- Development;
- Deployment;
- Maintenance.
Based on the relationship the client company and the outsourcing partner will have, there are 3 relationship-based outsourcing models:
- Staff augmentation - when the client company leases developers from the outsourcing partner for in-house projects to fill a skill gap in their internal team.
- Dedicated teams - when a client company hires a dedicated team from the outsourcing partner for a defined scope of work. The dedicated team may or may not work with the in-house team. The dedicated team reports to someone in a managerial position from the client company.
- Project-based - when a client company hires an outsourcing partner to complete an entire project, with the responsibility for the completion of the project resting on the outsourcing partner. The outsourcing partner forms the team(s), does the planning, and is responsible for all project management responsibilities.
Software development companies are businesses that design, develop, build, and maintain applications, frameworks, and other software technology.
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