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How to Become a Freelance Data Scientist (pt. 2)

In part 2, we lay out a clear road map for becoming a freelance data scientist and share 13 career-boosting tips for freelance data scientists taking their first steps down this exciting path.
Apr 2022  · 17 min read

Data Scientist working from home.

In part 1, we covered the pros and cons of choosing this path, discussed the various hard and soft skills you’ll need, and took a look at some of the best platforms to connect with potential clients. In part 2, we will outline the specific steps you’ll need to take to begin your journey, as well as provide a list of tips for beginners.  

A Complete Freelance Data Science Roadmap 

The following freelance data science roadmap is a useful guide to help you on your freelance journey. You don’t need to start from step one - you can jump directly to the one that matches your current experience. Otherwise, if you have no experience and are starting from scratch, you can start at the beginning. 

  • Start Learning Python or R
    Python and R are programming languages that are widely used by data scientists. We suggest you start with Python since you will be able to find way more opportunities as a beginner. Start learning Python with DataCamp’s Introduction to Python course. If you already know the basics, take our quick Python assessment and we will provide you with a personalized learning plan so that you can focus on gaining the skills you need the most. You can also check our Writing Functions for Product Analysis project, which will give you experience in writing clean and maintainable Python functions.

  • Gain Advanced Programming Skills
    Learning the basics usually won’t be enough to get your first job. You should get familiar with Python’s popular programming packages like NumPy, SciPy, Pandas, Scrapy, Matplotlib, etc. You should also know the theory behind them and practice data structures, algorithms, and object-oriented programming.

    You can improve your Python skills by taking our Intermediate Python course. We also offer you hands-on experience with our project Investigating Netflix Movies and Guest Stars in The Office.

  • Learn SQL
    Now it’s time to learn SQL (Structured Query Language) and relational and non-relational databases. With this, you will be able to learn how to retrieve, write, and manipulate data in databases.

    Start learning Python with DataCamp’s Introduction to SQL course, which will teach you the basics like how to filter, group, and sort data by writing efficient and optimized database queries. Or if you already know the basics, take our quick Data Analysis in SQL (PostgreSQL) assessment and we will provide you with a personalized learning plan.

  • Learn How to Visualize Data
    In this step, you should get familiar with some of the visualization libraries in Python and practice the most common techniques.

    Start learning with DataCamp’s Understanding Data Visualization course, which will teach you how to choose the best visualization technique for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots, and bar plots. If you have more advanced data visualization skills already, try An Introduction to Data Visualization with Matplotlib with lessons in time-series plotting, quantitative comparisons, and statistical visualizations. By taking this course, you will get hands-on experience with Matplotlib, one of the most popular packages for data visualization, and improve your Python skills.

  • Create Your First Freelancing Profile
    You are now ready to apply for basic tasks. Choose a freelancing platform and create your profile. Set your hourly rates and start applying for basic Python and visualization jobs.

  • Try Harder
    It may take time to get your first job and you may get frustrated, but don't give up. Apply for as many simple tasks as possible. Get in touch with the clients. Even if you can’t get a job yet, use this time to get familiar with the platform and the kind of tasks shared in it, and practice talking with clients. After you secure your first job, others will follow. Even if it takes a few months, be patient and keep trying.

  • Close Any Gaps in Your Mathematical and Statistical Knowledge
    You may need to expand your existing mathematical and statistical knowledge to be able to understand the basics of data science.

    Start learning with DataCamp’s Introduction to Statistics in Python, which will teach you the basics like simple probability calculations, distributions, and central limit theorem. If you already have more advanced probability and statistics skills, try Statistical Simulation in Python with lessons in simulations and probability distributions. You will also get hands-on experience in Python’s NumP​​y package.

  • Time to Move on to Learning Machine Learning
    Once you reach this level, you will feel comfortable getting to know the basics of machine learning. Don’t forget to test your new knowledge in sample projects in order to get comfortable applying machine learning where possible.

    Start learning with DataCamp’s Understanding Machine Learning, and AI Fundamentals, which will teach you the basics and help you to understand how machine learning works. If you have more advanced machine learning skills already, try Linear Classifiers, and Cluster Analysis courses with lessons in logistic regression, support vector machines (SVMs), and K-Means.

  • Learn the Basics of Deep Learning
    Creating deeper networks or using the existing pre-trained ones may help solve a problem more successfully. That’s why learning the basics of deep learning is important in data science.

    Start learning with DataCamp’s  Introduction to Deep Learning course.

  • Update Your Profile
    Now that you have gained more skills, it would be a good time to update your freelancing profile with your new abilities and experience.

  • Focus on Sample and Personal Projects
    You may still be having a hard time getting your first freelance job. It’s totally fine. At this point, you should probably shift your focus to working on sample projects or, if you have any project ideas in the data science field, it can be great motivation to gain more experience by working on these instead.

    Subscribing to articles about new technologies can also help you keep up with any updates in the field. Client meetings are not always just about their projects, and you may often find yourself in conversations about new technologies and trends. Being able to hold a conversation on such topics can help you greatly improve your relationship with your clients and give them a sense that you are truly engaged in your field.
  • Check the Available Jobs Daily or Hourly
    Finding the right job for you will require effort. Unfortunately, being a freelancer without client reviews will put you at the end of the queue when clients are looking for new candidates. You should be checking for new jobs daily or hourly, if possible. If you apply to jobs earlier than other freelancers, you will be seen first. 
  • Keep Your Clients Happy
    It is sometimes useful to check your clients’ previous job posts and offer them suggestions or ideas, even if they’ve already assigned the roles to someone else. Your clients may appreciate it and might be more likely to keep you in mind for future jobs.
  • Start Your Business Legally
    At this point, you will probably have realized that you can get freelance jobs if you try hard and deliver them successfully. Now you are confident about starting your freelance business legally. Do some research about taxes, freelancer fees and any other legal requirements in your country. Then you can officially start your business and claim the payments that have been stored in your favorite freelancing platform until now. 

13 Tips for Beginner-level Freelance Data Scientists

  1. Choose a Freelancing Platform and Stick to it
    It’s recommended to choose a freelancing platform and commit to it because the number of reviews and referrals you get on a platform will be key to securing other jobs and therefore ensuring your income. It takes time to make your freelancing profile powerful, so you will need to make an effort. Especially during the first year, your earnings can increase exponentially. If you divide your effort into several platforms, you may end up making a bigger effort for the same amount of success or even less.

  2. Create a Great Looking Profile
    When freelancers apply for jobs, clients evaluate the candidates by checking their profiles. Yours needs to stand out among the rest and be appealing to the companies you apply for, both in terms of what kind of information you provide and also your method of working. You should be displaying your experience in detail, including your university degrees and certificates, previous companies you worked for, and the roles you have performed.

  3. Start with a Low Hourly Rate
    When you first create your account on a freelancing platform, you won’t have any reviews or referrals, so you will need to prove yourself first. Start with a rather low hourly rate and focus on getting good reviews first. The rate that you can ask for depends on several parameters, like the country of residence of both parties, the freelancer’s experience, and the client’s budget. It is recommended that you research the hourly rates of other freelancers too to help you decide on your own initial hourly rate.

  4. Be Respectful
    Always be respectful while having a conversation with your clients. You will need to negotiate with them at times, but your priority should always be to keep them happy and satisfied.

  5. Don’t Promise a Specific Accuracy for Probabilistic Tasks
    Data-related tasks are often based on probability. You may need to apply machine learning and you may not know the data very well, or the client may not have shared a dataset with you. Even if you do know the data, you won’t be able to accurately predict the minimum accuracy for your tasks, unless you have already developed your solutions. However, the real-world problems or the data you are provided with may be different from what you have worked with before.

    You may be tempted to promise 99% accuracy for a task in order to get your first job, but you shouldn't put yourself in this position even if you have completed a similar task before. There is always a risk that something could go wrong and you may not be able to deliver on your promise.

  6. Let the Clients Know What You are Working on
    It’s better to keep your clients informed. If they don’t ask for it, you shouldn’t be spamming them, but it is always good to give them information about the steps you are taking and to talk about your ideas and what you will be working on next.

  7. Apply for Jobs Within Your Own Capabilities
    You will be agreeing on terms in binding contracts with your clients. Don’t apply for jobs that you are not sure you can accomplish. This doesn’t mean that you shouldn’t be confident and apply for roles out of your comfort zone, however. Even if you’ve never worked on a similar task before, you can still apply for those that require your skills and research. You don’t have to know everything beforehand, and taking on new roles that you’ve not done before is a great way to learn. If you think that you can complete a task, then you should apply for it.

  8. Provide Extra Work
    As already mentioned, if you are new to a freelancing platform, you should be considering getting good reviews first. After you complete your task, it can be a good idea to provide some extra assets, even if the client didn’t ask for them. For example, you could prepare a document that explains your work and architecture with visuals. This could be a reason for clients to give you positive reviews and referrals.

  9. Ask for Feedback and Referrals
    As a beginner freelancer, you may have a hard time when asking for referrals or feedback. However, if you think you did a good job, there is nothing to worry about. Most clients are more than happy to leave feedback, especially when you’ve helped them out and done your job well.

  10. Protect Your Physical and Mental Health
    As we know, working as a freelancer has some disadvantages. For example, freelancers usually work alone and from home, which can make them feel lonely. Also, this can lead to a rather sedentary lifestyle which may have a detrimental effect on their health and fitness. Always make your physical and mental health a priority.

  11. Keep Improving Your Language Skills
    If English is not your native language, it can be a good idea to improve your English proficiency. The more confident you feel with the language, the better you will be able to communicate with your clients, which can be a key skill that job posters look for during the selection process.

  12. Be Confident
    Because you are providing a service, you need to be confident about your ability to provide this service. As a first time freelancer, you may see your client as some kind of supervisor, but this is a rare dynamic to find in the relationship between a freelancer and their client. You should feel in a position to suggest improvements and guide them through the process; you are the expert after all.

  13. Do Not Give Up
    You may find it difficult to secure your first freelance job. The first one is always the hardest, and it can certainly feel overwhelming, but don’t give up. Improve your profile, work on your skills, and try to apply to jobs early so that you’re at least one of the first five applicants. Keep trying, and you will eventually secure your first role, after which others will surely follow.


In the ever-changing and developing world of technology, we are also changing and developing ourselves. Regardless of our age and level of experience, access to the internet provides us with unlimited possibilities when it comes to choosing and developing our own careers. Working as a freelance data scientist is an attractive career path for many, as it provides a lot of room for flexibility and self-growth.

By reaching the end of this article, you have taken your first step towards becoming a freelance data scientist. Keeping in mind the information given here, we recommend you plan your next steps and work hard to achieve the qualifications of your dream job and lifestyle. 

Starting a new career can be difficult, and so at DataCamp, we aim to make your journey to becoming a freelance data scientist as easy and enjoyable as possible. If you'd like further resources to assist your journey, check out our Data Scientist with Python Career Track and our Data Scientist Certification.

How to Become a Freelance Data Scientist FAQ's

How much do freelance data scientists make?

The earnings of freelance data scientists are highly dependent on their skills, experience, and good reviews. The range between junior and senior data scientists is quite wide. Hourly rates can vary from $10 to $300 per hour. According to this research, on average, novice data scientists charge around $50 per hour, and experienced ones with a Masters or a Ph.D. degree charge around $100 per hour.

Do I need a university degree to become a freelance data scientist?

In part 1, we went over the skills that all freelance data scientists should have. In university, you can obtain most of the required hard and soft skills, which means that if you have a degree, you have proof that you learned those skills. However, if you get this knowledge from a boot camp or on your own via educational videos, that’s also fine and, if done correctly, it can be enough to secure and successfully deliver data science jobs to a high standard.

As already mentioned, the most decisive factor in this profession is to have enough positive reviews in your profile. You will gain the trust of most clients when they check your reviews, but some clients may require you to have a Bachelor's, a Master's, or even a Ph.D. degree. Having a degree will open a lot of doors for you and make you feel more confident. In any case, not having one won't be a major barrier to success, as long as you are good at what you do.

How long will it take to get my first freelance job?

It depends on your skills and the effort you put into your job search. If you really apply yourself, it may take from a couple of days to a couple of months to land your first job. One of the first steps is to have an informative profile with all the details about your formal education and experience. It’s also helpful to write a nice bio, so clients can get an idea of who you are.

It’s recommended to start with small projects and the goal should always be to get positive reviews. Platforms encourage this system as well. For example, if you get around 7-8 reviews on Upwork and you complete them successfully with a 100% score, then Upwork assigns you a “Top Rated Freelancer” badge which highly increases your chance to get new jobs and bigger projects.

Where do I apply for freelance data science jobs?

We mentioned a couple of freelancing websites in part 1. These provide a platform for interaction between freelancers and clients where clients can post jobs and freelancers can apply for them.

The top three platforms for data science, which are evaluated by the number of active data science job postings and the number of highly skilled active freelancers, are Upwork, Toptal and Fiverr. You can easily create a profile on these platforms. However, some of them do not allow you to directly apply to jobs and may require you to pass a technical skill interview and English proficiency test beforehand. Some others, however, just verify your identity for security reasons and to validate your payment and tax information. After that, you can directly apply for as many jobs as you please.

Several platforms have fees for applying to jobs, but they are usually rather small amounts. Additionally, when you first create your profile, these platforms often offer you some free job application tokens to get you started. If you want to apply for more jobs, then the platforms require you to pay for these tokens. In some cases, like Upwork, if you have good communication with clients and you respond to job offers, the platform will give you free tokens in exchange for being an active freelancer.



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