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Hiring in-house data scientists vs. Byteflows? Ans: Do both.

Updated: Jul 6, 2020

Here are few things to consider when deciding on whether to build an internal team or bring in the Byteflow Data Science team for your projects :


A full data science team consists of at least one Senior Data Scientist ($175K+), a Junior Data Scientist ($125K) and a Data Engineer ($175K+). Full Cost: $475K + Benefits.

Many projects that Byteflows engages is start with as little at $20K for prototyping. Scaling up the project to enterprise level will bring the cost up to $200K.

Eventually, you will need someone internally to maintain the project. However, you now know exactly the kind of skills this person will need and we will help you attract the right candidate.

Long term maintenance

As we mentioned above, you will need internal personal to maintain projects in the long run. When you are starting the project however you will not know what those skills will be. Building skills are different than maintaining.


Whether you already have a data science team or are looking to build a new team, focus is important. Are you already working on other projects such as growing the business? Is your current analytics team busy with other priorities?

Let the Byteflows team take over some of your projects so you and your team can stay focused on current priorities while quickly experimenting and building prototypes on the side to later evaluate for ROI.


Is getting to market important for you? If so, our full data science and engineering teams will take on the projects and can go full speed to make sure your product reaches markets quickly.

Expertise pool

Does your project need a data scientist with a very specific set of advanced skills, such as NLP? Or does it require a little bit of everything?

With Byteflows you will access to a versatile team which possesses the following pool of skills: 

  • Data Architecture, Cloud Computing

  • Deep Learning (on GPU), Machine Learning

  • Computer Vision

  • Text Analytics. Advanced NLP

  • Scientific research (PhDs in Physics, Math, Neuroscience, CS)

Domains and case studies in brief:

Hedge Funds I: Deep Learning Models building to predict near-future price directions, trading time interval 2-10min.

Hedge Funds II: Data scraping and sentiment analysis to analyse the sentiment and over 100 stocks in several news organizations and blogs.

Insurance: A simulator to help program directors achieve high Star ratings on state official quality measurements.

Hospitals: Patient AI Referral Bot (PAIRT) identifies best fit patients for specific rehabilitation institutions to offer a bed to based on bed availability and patient historical information.

Healthcare: Research & development working alongside medical doctor researchers to help researchers better diagnose patients with bipolar disorders

Politics: Sentiment analysis based on twitter feed by state per candidate.

National Intelligence & Security: Gaining insights from large data sets to identify individuals of high risk. Developed a metric identify risk levels: low to high. .

Academia: Developed AI courses for select departments and research departments

NGOs: Impact measurements, data flow optimizations, data visualization.

Set up a call today to see if you qualify for some of our data science services:

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