Freelance Data Science: Pros, Cons, and How to Get Started

Data science freelancers are part of a growing gig economy, which is defined as a labor market that is tied to freelance work, short-term contracts, and other flexible work arrangements. People usually use this work to supplement income, and they largely rely on digital platforms to connect with employers. ¹ In 2020, freelancers comprised approximately 36% of the U.S. labor force and contributed up to $1.2 trillion to the economy.²

Over the past few years, remote work became increasingly popular (and necessary) to help protect workers’ health. However, a recent workplace survey indicates that a high percentage (71% of respondents) would still opt to work from home instead of a pay raise or promotion.² Since so many employees are ready and willing to work remotely, this greatly increases the number of prospects for companies that are hiring, as they can now recruit top talent from almost anywhere.

In the technology sector, there is high demand for talent around the world. Landing a job in data science, for example, is still competitive, but more companies are willing to hire data science freelancers to fill talent gaps while supporting their need for work-life balance. ³ They also can hire freelancers for roles that don’t require them to come into an office, helping them save on other costs.

If this is your first time branching out as a freelance data scientist, or if you're just considering the switch, then you'll immediately recognize some differences from past jobs. This post explores what freelance data science is, the advantages and disadvantages of contract work, how to become a freelance data scientist in the gig economy, and advice for succeeding as your own boss.

Advantages of Freelance Data Science

Before deciding whether to make the leap into freelance data science, carefully weigh the pros and cons and make sure it’s the right career move for you. If you feel you're good at taking action to source clients, manage your relationship and communication with them, track your progress, and rely on your own skills to achieve what a client needs, then you'll be a great fit.

Whether you’re pursuing a computer science degree, just graduated, or are in between jobs, freelancing offers some distinct advantages over traditional employment. According to a recent gig economy study, tech workers identified flexibility as a major advantage of data science freelance work. ⁴ About 66% said they plan to stick with freelancing for the foreseeable future.⁴

Greater autonomy to accept projects that align with your personal interests and values is another perk of freelance work, as well as time flexibility and eliminating stressful commutes. Finally, freelancing gives you the chance to work on a variety of data science projects, allowing you to quickly create a portfolio showcasing your diverse expertise.

At first, you may have to roll up your sleeves and work longer hours to get established. But with each well-executed project, you are building a reputation for high-quality work and dependability. With that track record of success, you will be able to negotiate higher rates based on the value you bring, as well as the project scope and complexity, deadlines, and deliverables.

Disadvantages of Freelance Data Science

Data science freelancing has its challenges and tradeoffs. For example, you may have more autonomy and flexibility, but more responsibilities and almost no job security. If you can switch gears and become your own boss, the greater the odds of your being successful and achieving career growth—and you will pick up valuable management skills along the way. .

Freelance challenges and obstacles include:³

1. Unstable income: Since you are no longer earning a steady paycheck, you will need to continuously market yourself through advertising, referrals, and testimonials
2. Administrative tasks: Reviewing contracts, negotiating pay rates, and educating yourself on self-employment tax laws could add more hours to your workday
3. Employee Benefits: Health insurance, retirement plans, and vacation will not be provided by your clients, so will need to make your own arrangements
4. Flying solo: Client meetings may provide some interaction, but you could feel more isolated, stressed, and unmotivated without regular team collaboration

Before deciding whether to make the leap into freelance data science, carefully weigh the pros and cons and make sure it’s the right career move for you.

Steps to Become a Freelance Data Scientist

Consider the following tips to begin your freelance career.

Networking and Building Presence

Building awareness of your freelance business takes time, but it will pay off. The key is to find the right niche to match your data science knowledge and skill sets. One data scientist reported how he started working as a freelance data scientist after publishing a clustering model and related tutorial on Medium.⁵

Here are a few ways to get started:

• Gain visibility by actively sharing industry news and tips on networking platforms
• Join data science groups and attend industry conferences and events
• Create portfolios on freelancer sites, such as Fiverr, Freelancer, and Upwork
• Write and publish data science articles on a blog

Finding Opportunities

Don’t wait for clients to approach you—start marketing yourself and your services. If you’re interested in a specific company or organization, network with current employees and sales and hiring managers to learn about hidden data science contracts or remote work. Often, these opportunities are not posted on job boards. Finally, ask satisfied clients to provide testimonials about your impressive work ethic, attention to quality, or ability to overcome challenges with grace. The more you do to distinguish your brand as a freelancer, the easier it will be to attract new clients and win their business.

Crafting Effective Proposals and Bids

As a freelancer, your mission is to find and apply for varied and interesting work and win over clients. In a competitive market, a well-crafted, client-focused proposal is essential to that mission. To increase the odds of your proposal being a slam dunk, tailor your expertise to the specific project, show that you have a deep understanding of their unique needs, and make the case that you are hands down the best choice.

When drafting your proposal, anticipate and address concerns, such as whether you have the capacity and expertise to handle the project, ways you will make the client’s life easier, and any prior knowledge or connection you have to the company. Be sure to highlight the technical skills you have, such as programming languages, machine learning, data visualization, and statistics.

Key elements to include in a freelance proposal:⁶

• Overview: Grab the prospective client’s attention and provide a high-level view of what value you would bring to the client’s business
• Problem statement and solution: Clearly communicate the client’s problem and outline a solution that sets you apart from the competition
• Pricing: Present fees that are fair, transparent, and easy to understand
• Timelines: Specify a reasonable project timeline that considers client needs and deadlines for tasks and deliverables.
• Next steps: Include a strong call-to-action, making it easy for the client to hire you or contact you with any follow-up questions

Balancing Multiple Projects and Time Management

Being your own boss requires a focus on finding the right balance between administrative tasks, project work, and leisure time. When you are first starting out as a freelancer, it can easily be feast or famine, where you accept too many projects or accept offers below your value in the marketplace. This situation can lead to being overwhelmed and stressed.

Here are some steps to effectively manage your time and avoid burnout:⁷

• Automated billing: Reduce time spent chasing after client payments and ensure a steady income stream that can cover your bills for at least one month
• Do your research: Determine fair compensation for projects by checking sites, such as Glassdoor and BuiltIn
• Work-life balance: Unplug from work email during off hours and make time for activities you enjoy and vacations with family and friends

Invest in a Bright Future in Data Science

For over 70 years, the sole mission of New York Institute of Technology has been to create career-oriented, technology-focused degrees. The Online Data Science, M.S. at New York Tech has the flexibility for working professionals who want to advance in their career without interrupting it. Within ten months, you’ll have the critical knowledge, skills, and experience you need to gain an edge in the field.

If an advanced, future-focused data science education sounds right for you, set up some time to talk with an admissions outreach advisor.