Top 10 Platforms to Get Market-Best Freelance Data Scientist

While full-time data scientists have to be paid for the idle time also, with freelancers it is only a gig-to-gig thing.

'Data-driven decisions' is a new catch-phrase in business circles. If you understand what it means to say, 'devil lies in the details', the thought of hiring a data-scientist team that cannot see the devil even just for once, will definitely send jitters. This is how data and the details therein hold importance for making an informed decision. Apart from that, it is not very cheap to hire a data scientist, as it is one of the hottest, in-demand positions in the job market. According to Glassdoor, hiring an in-house data scientist will cost you around $65,000 annually. While full-time data scientists have to be paid for the idle time also, with freelancers it is only a gig-to-gig thing. Here are the top 10 platforms to find the data-science gig workers who can match up to your requirement.

1. Toptal:

It is one of the premier sources of freelance data scientists known for its strict vetting process. Only 3% of freelance data science engineers get to feature on this website. It is not simply a post-your-resume and forgets hiring website. It tests applicants for their communication skills apart from testing their subject expertise, especially SQL and Python knowledge. Engaging Toptol for freelancers is risk-free and often the right match is found within 48 hours.

2. iCrunchData:

iCrunchData is an award-winning platform known for its content and job postings. If you are on a lookout for hiring freelance data scientists, this is the right platform for you. As per Glassdoor reviews, companies have fairly good experience with iCrunchData in IT and Engineering domains. Their innovative approach, extensive reach, and unique positioning can help your company a lot not just in talent acquisition but also in advertising strategies.

3. Stack Overflow:

A knowledge-sharing platform, established in 2008, has grown leaps and bounds to become one of the top five most visited websites. The fact that more than 100 million people come to Stack Overflow's public platform every month, should be a good enough factor for companies to consider while hiring freelance data scientists. With diverse skill sets in the offing, it is a place where you have the chance to choose the most versatile data-scientists who have deeper insights into a wide range of subjects.

4. Open Data Science Jobs:

Open Data Science Jobs, a recruitment portal with data-science only postings is ideal for companies looking for specialized data-science freelancers. In fact, it is one of the largest among data-science-only job portals that some big-ticket companies like Bose, Amazon, and Accenture have utilized for hiring data scientists. Their website gets 15,000 unique visits a month with each job averaging 200 views in the very first week.

5. Kaggle:

It is a popular online community for data scientists and machine learning experts. Like Github it is a knowledge-sharing platform where participants share data sets, collaborate for coding, and participate in data-science competitions. With 5 million users, and their profiles having information of their discussions on the technology platform, it gives the recruiters a wide choice choose from, for prospects with in-depth knowledge of the domain concerned.

6. Github Jobs:

Github is the world's top technology-based platform for technical experts to participate, share and contribute to different technical projects. The candidate's expertise becomes well evident in their profile in terms of followers, contributions, and repositories. The candidate's popularity can be thoroughly assessed by simply checking how many people have 'forked' (i.e., seen as valuable by other developers) their projects. The three main things one has to check to find the right candidate are their followers, language, and location. By keying in certain keywords right, there is every chance that you can find your jig-saw fit.

7. Upwork:

Upwork is one of the most popular freelancing platforms on the internet if you are looking to fill job roles for immediate requirements. Though it has millions of registered users, the pool of freelancers is slightly smaller because of the platform's uncompromising selection process. With its advanced search filters, the tedious job of finding the right candidate for a specific job gets easy. On Upwork, the work seekers have a shiny badge displayed next to their profile, which gives the recruiter another quick way to sift for good candidates.

8. Gigster:

Gigster is one hiring platform where you can find the ensemble of a complete team, including, team managers, data leads, etc with a project analysis manager who can act as a liaison between Gigster and the company's data management team. They boast of having top-notch companies like Google, Microsoft, Stanford Univerisity, hiring freelancers through their platform. To date, it has garnered around $32 billion from Silicon Valley investors. Their vision statement clearly states that they believe in facilitating companies build their own DNA to create life-changing products – a cue for recruiters looking for that perfect match.

9. Simply Hired:

Just like Indeed and Monster, it is yet another general job board, which comes with loads of resources, from salary recommendations to hiring guides, with the differential factor being its low pricing. You can begin with searching for salary estimators and post within a hundred networks over hundreds of job boards within no time. Browse through the collated data science jobs by location and check if posting a job on Simply Hired is worth it at all.

10. Kolabtree:

Unlike other freelancing platforms, Kolabtree specializes in consulting services, instead of using pricing and freelancer quality as distinguishing parameters. Just in case if you are looking for only consulting services, this platform is the right choice. All their freelancers are PhD-qualified scientists, academics and subject matter experts who can help companies with their valuable expertise in solving complex problems.

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