7 Step Guide to Become a Freelance Data Scientist

The Ultimate 7 Step Guide to Become a Freelance Data Scientist that will help you land your first lucrative data science gig.

7 Step Guide to Become a Freelance Data Scientist
 |  BY ProjectPro

If you are tired of googling how to become a freelance data scientist, you need to relax because your search is finally over. In this blog, we have presented a step by step guide for becoming a freelance data scientist and a quick and easy way of getting hired as a freelance data scientist. So, take a backseat and simply continue reading our blog.

With COVID-19 restrictions forcing companies to lay off their employees, millions of individuals who lost their jobs decided to navigate a freelance career. The same holds for employees working as Data Scientists as well. Working as a freelance data scientist may not seem rewarding initially, but it is definitely a gratifying career option in the long run. As a freelance data scientist, you get to control your working hours and lifestyle. The benefits also include not needing to work all year long and getting to plan their hassle-free vacations.


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As per the Freelance Forward: 2020 report by UPWK, freelancers in the United States contributed $1.2 trillion to their economy during the COVID-19 pandemic. The report also revealed that about 75% of individuals who left their full-time jobs for a freelancing career earned more or similar when compared to their traditional employers.

As per the website 6figr, freelance data scientists’ salaries in India range from ₹12.0lakhs (~16k USD) to ₹23.9lakhs (~32k USD). These statistics clearly show that a data scientist freelance career will be monetarily beneficial. So, if this seems tempting enough and you wish to explore how to freelance as a data scientist, move ahead to the next section of this blog, where we discuss this in detail.

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How to Become a Freelance Data Scientist

How to Become a Freelance Data Scientist

Step-1: Explore the world of Data Science and Identify your bias

It becomes difficult to know every nut and bolt of all the application systems when it comes to Data Science. That is primarily because the field of Data Science has quite a lot of subdomains to explore. These subdomains include Data Mining, Natural Language Processing, Computer Vision, Data Visualization, etc. Depending on your bias among them, we suggest you master your skills in that domain by practising more and more.

Recommended Reading: How to learn NLP from scratch in 2021? 

But, you must wonder how a freelance data scientist knows what their bias is in Data Science? The answer is simple: Practice. You must explore the entire domain of Data Science by working on different types of data science projects. The more you work on different projects, the more you’ll be exposed to various subdomains of Data Science, which will open more doors of options for you.

“Jack of all trades, master of none”. 

The above quote nicely sums up what we are trying to convey in this step. A lot of companies these days are seeking candidates who specialise in a particular field. It holds true for freelance data scientist jobs as well. Thus, it is highly recommended that you first begin applying your skills to different projects in data science and then decide which subdomain is your bias. 

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Step-2: Diversify your skills and keep them up to date

Now that you have found your bias, the next step is to dig deep. You should master the specific subdomain of your choice by practising challenging problems. It will prepare you for upcoming complex problems that you might come across when working as a freelance data scientist. Also, it will help you save time and make you more efficient as a hired hand.

Another thing that you should keep in mind is to regularly track the new machine learning algorithms and data science techniques that are being introduced and practise a few projects around their implementation. This approach will keep your skills up to date and give you an edge over other data scientist freelance jobs applicants.

Recommended Reading: How to Become a Data Scientist | Data Scientist Career Path 

Step-3: Build an attractive Project Portfolio

"If you can't write your message in a sentence, you can't say it in an hour." -Dianna Booher 

With the help of the above quote by one of the famous communication experts, we want you to understand how important it is to present your skills concisely and attractively. Hiring managers have tons of resumes to scan through, and thus, the amount of time they spend reading a specific résumé is minimal. Hence, you must make sure that you design a neat résumé with short to the point sentences yet reflect everything you want to convey. 

Build an attractive Project Portfolio

Besides writing an attractive and succinct resume, you can also create a separate data science projects portfolio. This portfolio should highlight all the different types of data science projects that you have worked on, along with algorithms. Below is a format that you can use to showcase every project.

Project Title:

Programming Language Used:

Objective:
Algorithms Applied:
Inference:

As an example, consider the Data Science Project - Building a Credit Score Prediction Model to identify credit defaulters from our repository. Here is how one can add it to their portfolio.

Project Title: Credit Score and Default Prediction

Programming Language Used: Python

Objective: To create a model using the inputs/attributes that are basic profile and historical records of a borrower to estimate how likely it is that an applicant will have serious delinquency in the next 2 years.

Algorithms Applied: BoxCox transformation and Standardization, Neural Network as a Deep Learning architecture, Logistic Regression, Bagging and Boosting, Recursive Feature Elimination.

Inference: Used machine learning algorithms to build a system that will help banks identify borrowers that may have alarming delinquency rates in future.

Further, we’d like to suggest that you upload all your project-related files on websites like GitHub and add a hyperlink to them in the portfolio. Additionally, once you start with a GitHub Repository, ensure that you are uploading projects regularly and are an active user. Create separate folders for each project and upload IPython solution notebooks to showcase your code implementation. Make sure your code has been commented on well so that the hiring managers can verify your skills and experience easily.

Recommended Reading: 15 Machine Learning Projects GitHub for Beginners in 2021

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Step-4: Start Small!

When starting as a freelance data scientist, you must pay less attention to monetary benefits and focus on building your experience. So, initially, do not feel demotivated if you think you are not being paid enough. The road ahead will be fruitful and worth your patience. 

While applying for freelance data scientist jobs through websites like LinkedIn, Indeed, Naukri, etc. can give you the desired push to your career, you can also consider dedicated freelance data scientist websites like Upwork, Toptal, Fiverr, and Data Science Central that will help you land your first freelance data science gig.

Once you have served a few clients and diversified your skillset enough, add them to your portfolio. Also, you may request your clients to provide you with feedback so that you can add it to your portfolio for bringing in more clients.

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Step-5: Advertise your Data Science Skills!

There are a lot of different types of digital marketing that you can try, but two easy ones are social media marketing and Search Engine Optimisation (SEO). For the former, we suggest you maintain an active account on professional websites like LinkedIn. Invest time posting regular updates about your work and occasionally sharing it personally with your friends and family. For SEO, we suggest you write a few articles about your work on Medium. You must try to make them rank in the top 20 articles of Google search results for popular keywords.

Step-6: Build your Professional Network!

For this second last step, we recommend you make sure to connect with your clients on platforms like LinkedIn and keep in touch with them by sharing your work. Also, put in efforts to grow your professional network and do not hesitate to ask your connections for referrals. People on LinkedIn are primarily supportive and will not mind helping you.

Step-7: Keep Learning!

The last step is not to stop learning and continue exploring the exciting domain of Data Science. We understand there might be days when you may not be selected for a project you have longed for. On those days especially, do not sit back and wait for another opportunity to knock at your door; continue challenging yourself with more difficult Data Science problems.

Recommended Reading: How to Learn Data Science From Scratch on Your Own in 2021

Becoming a Freelance Data Scientist: Easy and Quick Way!

Drumrolls, please! Because we are about to share the most efficient learning path for turning your dream of becoming a freelance data scientist into reality. If you want to achieve your goal quickly, we suggest you try ProjectPro, a platform with access to over 120+  solved end-to-end projects in Data Science and Big Data. These projects are industry-relevant and have been prepared by a team of expert data scientists working at renowned multinational companies like Amazon, Netflix, PayPal, Uber, etc.

To make your learning experience smooth, the project solutions are curated as a series of short guided videos. Most projects' solutions follow a generic layout where the first few videos describe the project’s overall objective and business idea. The following videos contain a full explanation of the approach along with the code. And at last, you will find a nice summary of the project. 

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Freelancing as a data scientist can be quite challenging for beginners who have started exploring Data Science. As a newbie, it’s likely that you don’t know where to start. ProjectPro platform addresses this problem with a customized learning path for every user. This path will guide which projects they should start with and which ones they should learn next. Our projects take that into account as well because ProjectPro’s projects library has many beginner-friendly projects in different domains of Data Science, from Computer Vision projects, NLP projects to widely-used Python libraries projects like Keras projects and TensorFlow projects

With so many exciting features, we hope you won’t hesitate in supporting our claim that ProjectPro is a one-stop solution for all your worries if you are a beginner who wants to work as a freelance data scientist. Here are a few beginner-friendly data science projects that we recommend you look at and verify our claims yourself.

  1. Predicting survival on the Titanic

  2. Walmart Store Sales Forecasting 

  3. Kaggle Instacart Solution

  4. Churn Model using logistic regression

  5. BigMart Sales Prediction Solution using Python

  6. Credit Card Fraud Detection 

  7. Build a music Recommendation System Python using ML

The project repository is up to date with the latest algorithms and methodologies in Data Science with new projects launched every month. So, if you are someone who is looking forward to upskilling through learning by doing, we’d like to confirm that it is very much possible. 

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To further support our customers’ Data Science learning journey, we offer them one-on-one industry expert guidance so that any time they get stuck on a project, they can schedule a session to discuss with them.

FAQs

1. How much does a freelance data scientist make in a year?

According to the US Bureau of Labor Statistics, the average salary of a data scientist is $100,560 per year.

2. Do I need a permit to be a freelance data scientist?

No, you don’t need a special permit to start your career as a freelance data scientist. Check out ProjectPro Data Science Projects and Big Data projects if you are looking for a one-stop solution for how to be a freelance data scientist.

3. Is it hard to get work as a freelance data scientist?

Initially, there may be roadblocks that will be difficult to overcome but as you continue to work hard, you will gradually learn how to freelance as a data scientist.

4. How to become a data scientist freelance?

Follow these simple steps in case you are looking for a freelance job as a data scientist.

  1. Identify your niche in Data Science by working on various types of data science projects.

  2. Diversify your skill set by taking up challenging problems

  3. Keep yourself updated about the latest algorithms in the industry.

  4. Create a data science portfolio.

  5. Do not hesitate in taking up small projects initially.

  6. Advertise your skills on social media.

  7. Keep in touch with your professional connections through LinkedIn.

  8. Don’t give up and continue learning.

 

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