How to Hire Freelance Data Scientist in 2023
One of the essential goals of sourcing and using data is to help businesses make better decisions, so they can be at the top of their industries. To do this effectively, many businesses employ data scientists. These experts help to collect, visualize, and make sense of all kinds of data correctly.
By having access to data experts’ skills and knowledge, businesses can make more informed decisions based on the data they have and work through different data pipelines. In turn, this helps businesses make better propositions, create better products, and ultimately, meet customers’ needs better, using a competitive advantage.
Many businesses that want to invest in the benefits of data hire data scientists. Let’s look at a few of the top reasons for hiring data scientists:
- Data needs analyzing
Data must be read and analyzed carefully. This requires a professional understanding of how to read it and make data-driven findings.
- Data can enhance products and services
Data scientists can source essential insights from data that can be used to effectively enhance products and services to reach a bigger target market.
- Data creates better customer experiences
When data is analyzed correctly, it can produce important insights into the needs of customers. Using this can help businesses meet the needs of customers more accurately.
- Data can create new opportunities
Data scientists can use information sourced from data to see where businesses can expand and tap into new opportunities.
Top Industries That Can Benefit From Hiring Data Scientists
Today, data can be used to benefit almost any business in any type of industry. But some industries can gain significantly more from hiring expert data scientists. Some of these include:
Data is an important part of all areas of medicine and accounts for around 30% of the international data volume. Data is used in clinical trials, for predictive testing, electronic health records and disease registries.
- Big Tech
Tech companies use data science to enhance user experience, create personalized recommendation systems, develop innovative solutions, and more.
Data science in agriculture can help businesses develop data pipelines specifically for automation and fast scalability. For example, they can build machine learning models to predict plant diseases and weather conditions.
In the insurance industry, data scientists mine and analyze data for use in customer segmentation, risk modeling, lifetime value prediction, etc.
Data science can help businesses to improve customer service, enhance products, optimize production, and lower losses.
Data scientists can help create models to better understand the patterns of malicious activities and eventually help to predict them.
There are many other industries where data scientists can benefit different areas of businesses. Some other industries include law, traffic, communication, banking and education.
Services Data Scientists Can Offer
Data scientists specialize in a variety of tasks that can benefit businesses in different ways. Some of the most noteworthy services they offer include:
- Data Science and Big Data Consulting
Big data engineer experts review existing data architecture, explore data sources, and analyze data lakes. They can also assist with adopting the most effective data pipeline-building process, and viable options to manage data.
- Data Collection
Data science freelance experts can work through any type and amount of data. They can collect the voluminous data required for delivering useful insights.
- Data Preparation
Data scientists can perform data quality assessments to eliminate unsuitable data types and clean the data of any anomalies.
- Data Modeling
Data architects can build data models using precise tools and relevant data modeling techniques.
- Data Warehousing
Most expert data scientists can create layers such as ODS and OLTP to set up data warehouse infrastructures in the cloud or on-premise.
- Data Visualization
Data science freelancer experts can transform intricate data insights into visually appealing and usable forms.
- Data Training
Data training is an important part of data science. Most experts can leverage both labeled and unlabeled data to initiate learning models.
- Build and Deploy Machine Learning Models
Data science expert developers can build clustering, classification, forecasting and natural language processing machine learning models.
- ML Model Evaluation and Tuning
For ML model deployment, remote data science experts can detect any anomalies and resolve them by evaluating different metrics.
- Statistical Modeling
Data science remote developers have statistical skills and can create statistical models to analyze datasets for detailed insight interpretations.
The Difference Between Data Scientists and Data Analysts
When looking for data experts, it’s important to note that there are different professionals specializing in different fields. Two of the most popular data experts are data scientists and data analysts. Let’s explore the differences between these two:
Data analysts may spend more time working on routine analysis, and provide regular reports regularly, whereas data scientists may design how data is stored, managed and analyzed.
In simple terms, data analysts make sense of existing data, and data scientists work on new ways of sourcing and analyzing data.
Understanding the differences between these roles can help you hire the right candidates for the type of project or job you have available.
The Skills, Responsibilities, Methods and Tools of Data Scientists
Data scientists collaborate closely with distinctive stakeholders to reach different company objectives. Their job is to gather large amounts of data, analyze it, and then utilize tools to extract insights that may be used to increase productivity and efficiency. Some of the roles and responsibilities of data scientists include:
- Collecting data and identifying data sources
- Analyzing large amounts of data
- Working with business leaders to develop data strategies
- Discovering trends and patterns, while combining various algorithms and modules
- Presenting data using a variety of data visualization tools
- Creating analytics solutions for businesses
- Architecting, implementing, and monitoring data pipelines
To complete these tasks, data scientists typically have a rare hybrid of skillset. Some of their skills include:
- Excellent business acumen
- Ability to problem solve
- Curiosity and desire to learn
- Ability to work as part of a team
- Excellent verbal and written communication skills
- Expertise in programming languages such as Python and R language
- Managing and manipulating large datasets
- Expertise in data extraction and transformation
- Expertise in machine learning and deep learning
- Expert knowledge of various NoSQL databases
- Expertise in data visualization and architecture
The most significant methods and tools used by data scientists include:
- Statistical Programming Methods
Using tools such as SPSS Statistics, JMP, RStudio, OriginPro, Base SAS and Wolfram Mathematica.
- Neural Networks
Using tools such as Autoencoders, LSTM and GRU and Deep Q-network (DQN).
- Supervised Learning Algorithms
Using tools such as Support Vector Machines, Logistic Regression, Gradient Boosting and XGBoost.
- Unsupervised Learning Algorithms
Using tools such as Stochastic Gradient, Isolation Forest, Apriori Algorithm and Affinity Propagation.
The Best Sites to Hire Freelance Data Scientists
Today, several platforms can be used to find full-time and part time data scientist candidates suitable for your project. Each of them has their own unique benefits. Some of these include:
Fiverr is a global online marketplace designed for finding professionals such as freelance data scientists offering tasks at low costs. Fiverr is one of the cheapest hiring sites currently available.
Mobilunity is a popular outsourcing company providing access to a large talent pool. The team at Mobilunity is highly experienced and can assist with sourcing and hiring qualified candidates for a variety of data science projects.
This is an easy-to-use online job marketplace that specializes in offering freelancer data scientist experts around the world to collaborate with businesses at affordable rates.
Toptal is a platform that provides some of the best data scientist freelance candidates to work on projects. What makes this marketplace unique is that only the leading 3% of candidates make it through the vetting process.
This is a tech freelancing board that has a slightly higher price compared to some other job boards. Candidates are advertised across thousands of different sites.
UpWork is one of the most favored platforms to find part time data science freelancers. This platform gives you access to a shortlist of some of the top candidates available when you post a job. It also allows you to test and pay applicants through the platform.
Choosing In-House vs Outstaffing vs Freelance Data Scientists
When considering hiring data scientists, it’s essential to think about the hiring model. Today, there are many different ways to hire top candidates to work on different types of data projects. Some of the most popular hiring methods include hiring in-house teams, outstaffing and hiring freelance candidates. Let’s explore some of the differences:
|In-House||Outstaffing||Hiring Freelance Data Scientists|
|What is it?||Hiring in-house staff involves hiring workers to join an existing team in a physical location.||Outstaffing involves employing staff long-term indirectly through a third party.||Hiring freelancers involves hiring workers once-off, only when needed for a project.|
|Time involved||Hiring in-house workers can be time-consuming as talent may be limited.||Outstaffing companies can typically find candidates instantly, ready to be hired.||Finding the right freelancers can be a time-consuming task.|
|Cost involved||Cost depends mostly on average local salaries.||Outstaffing companies usually have set rates for candidates.||Freelancer rates may vary from country to country, and level of experience.|
|Dedication||In-house staff are dedicated to working only for one business.||Outstaffing data scientists are mostly dedicated to only one project at a time.||Freelancers often work on several projects at a time.|
The Cost of Hiring Data Scientists
When hiring data scientists, it’s important to consider the cost involved. The rate of these professionals varies largely from country to country and by level of experience. To give you an idea of what to expect, we explore the average hourly freelance data scientist salary of five different countries:
*Ukrainian salaries are provided based on Mobilunity’s Recruitment Team research on the local job markets. All salaries are net and do not include the service fee (in case of hiring on a dedicated team model). The salaries are provided for comparison purposes and could be not entirely accurate. Contact us to know the exact cost of hiring a developer corresponding to the required parameters.
From this data, it’s evident that some countries are much more affordable to hire remote data scientist candidates compared to others. For example, hiring experts from Ukraine costs a fraction of the price it will cost to hire the same experts from countries such as the USA and the UK. This is because Ukraine has a much lower cost of living, even though its workers are highly skilled and experienced.
Mobilunity: Reliable Provider of Data Scientists
With over 10 years of experience, Mobilunity is a leading outsourcing company offering talented workers, including data scientists, to businesses around the world. Mobilunity has access to thousands of talented workers that can collaborate with many different businesses, both big and small, in a variety of industries.
Mobilunity makes it very easy to hire workers. With us, you can simply hire part-time data scientists and pay for only the hours worked. By doing this, you can save money while getting access to top talent when required.
The team at Mobilunity has worked with many different businesses in a variety of industries. Some of our clients include Codename, 42Matters, Paidy, Qrates, and ServIT.
Our clients choose us because we have a fast and efficient approach to hiring. Our approach includes the following steps:
- Identifying and confirming your unique requirements
- Finding suitable candidates
- Interviewing chosen candidates
- Assisting with onboarding and ongoing support