Hire Data Science Developers

hire Data scientists

Looking to hire a skilled Data Scientist dev, but are already worried about the headache the process might cause? Hire with Lemon.io stress free!

Hire Data Scientists 

To better understand who a Data scientist is and why you would want to hire a data science engineer, let’s take a look at what data science is. Data science as a field works to extract knowledge from structured and unstructured data. On the surface, to do so, it uses algorithms, scientific methods, and systems. But dig deeper, and you will see that it combines statistics, computer programming, mathematics, and information technology (IT) to process and analyze big, intertwined amounts of data. And it is all done with one purpose – derive insights and make predictions about the real world.

What will we cover?

Are you dealing with large databases and are looking to make product predictions based on them? Then you should look into adding a Data Scientist to your team. 

Read on to find out more!

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Hemed K.

// senior machine learning engineer/ Senior Data Scientist

Senior Data Scientist with a theory base (Ph.D.), hands-on technical experience, and proven people skills. Hemed has achieved remarkable results working on a diverse range of ML models.

  • data science
  • flask
  • python

Nazariy P.

// lead software developer / head of engineering

Meet a man with various interests: Data Science, Machine Learning, crafting sweet code, playing multiple musical instruments, and chess. Impeccable English included.

  • data science
  • machine learning
  • +2 skills

What does a Data Scientist do?

Data Scientist analyzes and interprets large volumes of data generated and provided to them by data engineers. By doing so, they aim to identify similarities, trends, and patterns. With this information, businesses can now make better and more precise decisions, as well as create new products and optimize the existing ones.

Furthermore, a Data Scientist can also develop operational models using machine learning algorithms. These models help companies to forecast future outcomes based on current conditions.

Why hire a Data Scientist?

  • Data science experts are a valuable asset in any company when it comes to developing business strategies based on available data. As mentioned earlier, their main task is to analyze large volumes of data to extract insights and make market predictions;
  • Besides being able to build predictive models to forecast customer behavior and market trends, they can also develop algorithms for automated decision-making processes;

In other words, an experienced Data Scientist will work to help your businesses make informed decisions regarding product development initiatives, pricing structures, and marketing plans.

Challenges of hiring a Data Scientist

There are two major challenges you might be faced when looking to hire a Data Scientist for your startup. 


Number one is finding the right candidate.

This is challenging because a Data Scientist should possess both non-technical and technical skills, such as machine learning algorithms, knowledge of databases and programming languages, statistical analysis techniques, and decision-making. Since the desired skillset varies from company to company, it might be difficult to locate a Data Scientist with the necessary qualifications but also desired educational level and relatable past experience.


Challenge number two is fierce competition

Even when you locate the one and only Data Scientist, you might find it difficult to make them interested enough. Since the demand for data science professionals has grown exponentially over recent years, it became very competetive to attract the top Data Scientists these days. This makes it even more difficult for startups with limited budgets because now you are competing with tech giants who are able to afford higher salaries and sweeter benefits.

On top of that, if you are a company located outside the lines of Silicon Valley or New York City, aka tech clubs, it could look like mission impossible due to lower salaries in other regions of the USA and the globe. 

Do these challenges sound like there is no way out? Hang on there! We’ve got a solution.

What you have to do before hiring a Data Scientist?

  • Understand why you are looking to hire a Data Scientist.
  • Define the role.
    To do so, draft a job description. In the post, make sure to clearly articulate your expectations for a Data Scientist and outline the key qualifications, skills, and responsibilities that are required to perform successfully in this position in your company.
  • Mark a budget.
    Evaluate how much you can afford to spend in order to hire a Data Scientist before beginning the recruitment process. You have to do so in order to avoid surprises down the line or when it comes to negotiating salary and benefits packages.

  • Identify the hiring model.
    Are you planning to hire directly to your company or incorporate bidding platforms into your hiring process? Or maybe you are aware of platforms for vetted developers, like Lemon.io, that can save you both time and money in your business journey.
  • Craft an assessment plan.
    By that, we mean to plan your candidates’ evaluation. How many steps will there be? Are you planning on conducting live interviews? Will there be a test task to evaluate technical skills? Don’t skip test tasks since it mirrors Data Scientists’ daily routines and tell you whether they will be a good fit for the job. If so, consider adjusting a task according to each candidate’s experience if possible. 

Skills to assess in a Data Scientist 

Remember we discussed that the ideal Data Scientist would usually possess technical and non-technical skills? Here is the list for you to be able to assess their skill set better. 

  • Data science, mathematics, statistics, or computer science degree;
  • Good knowledge of SQL, Python and R;
  • Experience with machine learning algorithms;
  • Knowledge of ML techniques like regression analysis, classification models (decision trees/random forests), and clustering methods (K-Means);
  • Hands-on experience with the following libraries: Pandas, Numpy, and Matplotlib;
  • Experience with database management systems like MySQL and MongoDB; 
  • Statistical skills like collection, analysis, and interpretation of large volumes of numerical data;
  • Knowledge of Big data technologies like Apache Spark and Hadoop;        
  • Expertise in business analysis; 
  • Familiarity with Deep Learning and AI;
  • Experience with visualization tools (e.g. Tableau, PowerBI, Metabase, QLik)
  • Analytical mindset. 
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What’s the cost of hiring a Data Scientist?

Let’s take a look at San Francisco first. An annual salary for middle to senior-level Data Scientist varies between 118k to 188k USD, with an average annual for both levels setting between 140 to 150k USD or an hourly rate from 66 USD to 71 USD.

Moving west, we got New York City. There, the annual salary for a middle-level to senior-level Data Scientist developer starts at 107k, with the top one being 174k USD. On the other hand, the median annual for both levels varies between 132k to 140k USD or an hourly rate of 62 USD – 66 USD. 

Crossing the border and flying to the opposite side of the world, in Sydney, Australia, the annual salary for the same level Data Scientist sets between 70k USD to 107 USD or a median yearly salary ranging from 78k USD to 93k USD or hourly rate of 37 USD – 44 USD per hour. 

Flying back to Europe, in London, UK, the yearly salary for middle to senior-level Data science developers greatly varies between 58k USD and 125k USD, with an average annual setting between 77k to 93k USD or an average rate per hour for 36 USD to 44 USD. 

Finally, traveling to lemonverse of Lemon.io, you can find middle Data Scientist at 45 USD – 50 USD per hour, while senior Data Scientist will cost you between 55 USD to 60 USD hourly.

Why hire a Data Scientist with Lemon.io?

  • Rates.
    We will help you find a dedicated remote Data Scientist without ripping your wallet apart;
  • Vetted software developers from around the world.
    Not only do we have a thorough vetting procedure in place developed explicitly for you to work with the best devs, but also our Data Scientists come from different countries. That is to say, no matter where you are located, be sure we will find you the right fit according to your time zone, budget, and requirements;
  • Custom matching.
    It takes us 48 hours after your request to match you with the right candidate. Considering that average recruiting can stretch up to six months, 48 hours sound like seconds; 
  • Stressless onboarding.
    With your success at the core of our mission, our Customer Success team will make sure to put you into action seamlessly; 
  • Weekly reports.
    Lemon.io provide you access to the reports where you will be able to see how many hours your developer worked on your project, as well as what tasks have been completed;
  • Support throughout the project.
    Shoot us an email, and we will immediately return to you, making sure any issue or question you might have will be resolved and answered;
  • Quick start.
    At Lemon.io, we know how much you want to keep on going with the business and development and spend as little time as possible on all of the bureaucracy. We got you covered! We have developed our paperwork in a way that you don’t have to sign tens of papers to start working with your dev unless desired otherwise, of course.


  • When should I hire a Data Scientist?

    When you have identified specific business issues that can be solved with the aid of advanced analytics and machine learning techniques, that is the best time to hire a Data Scientist. Consider hiring a Data Scientist if your business requires predictive modeling, analysis of sizable datasets, or automated decision-making.

  • Can a developer be a Data Scientist?

    Yes, after completing additional education, a developer can become a Data Scientist. Moreover, developers often possess the coding and analytical skills needed for data science. They are also familiar with programming languages like Python or R that are used for data analysis and machine learning tasks.

  • Are Data Scientists in demand?

    Yes, Data Scientists are in very high demand. As a matter of fact, according to the US Bureau of Labor Statistics, employment of Data Scientists is projected to grow 36 percent from 2021 to 2031. This increased demand comes as businesses and organizations rely more heavily on extensive data analysis and predictive analytics when making decisions related to their operations or the products/services they offer customers.

  • Is a Data Scientist an IT job?

    Yes, it is! Data Scientists are similar to IT professionals in that they both focus on assisting their organization. However, Data Scientists specialize in utilizing data to create business value rather than a specific technology. They have extensive knowledge of managing large amounts of information and use this expertise to achieve beneficial outcomes.

Still have questions?

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