The interest in data science services is amplifying daily, with trends like Big Data, machine learning, and analytics gaining traction. Harvard Business Review’s declaration of data science as ‘the sexiest job of the 21st century’ in 2012 set the stage for exponential growth. For example, the Royal Society noted a 231% increase in UK job postings for data science from 2013 to 2018. By September 2019, LinkedIn reported nearly 29,000 job opportunities in the US, over 20,500 in the EU, and just above 6,000 in the UK.
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Demand for Data Science Services across the Globe
What were the hot data science skills in 2023? An examination revealed that abilities in machine learning, analysis, statistics, and math were prominently mentioned in job postings.
Key Data Science Skills in 2023
Many companies also showed interest in professionals with expertise in deep learning and NLP. A survey of high-demand technologies placed Python at the forefront, followed by R, Hadoop, Spark, and Java.
Emerging Data Science Technologies
So, given this plethora of technology choices and the high demand for data scientists, how does one locate an outstanding provider of data science services? Here are five essential guidelines:
- Determine Your Objectives
Assess your business needs. Understand whether you require Big Data analytics, business intelligence, third-party integration, or customized development.
- Select the Location Thoughtfully
The growing need for data science professionals makes local scaling tough. Outsourcing data science agency might be the answer. Evaluate the quality, quantity, and expertise available in different countries. Consider options such as onshoring, nearshoring, and offshoring.
- Evaluate the Tech Talent
Pay attention to the skilled professionals in a particular location and the competition for them. For example, Eastern Europe offers a solution to Germany’s immense competition for its 22,000 professional data scientists.
- Set Vendor Selection Criteria
Be precise about what affects the vendor selection, such as:
- Technical and industry knowledge
- Relevant experience
- Company size and reputation
- Price
- Portfolio
- Identify the Right Tech Stack
Consult with your vendor to ascertain the technologies and tools needed for your project. This may include R, Python, Java, Scala, Hadoop, Cassandra, Matlab, Tableau, and other machine learning classification algorithms.
Concluding Thoughts
The enormous quantity of daily data collection ensures that demand for top-notch data science services will continue to rise. Data science emerged as a vital skill across multiple industries, leading to a surge in companies seeking dependable data science vendors. These guidelines aim to support businesses in leveraging data science effectively, transforming raw data into actionable insights, and elevating operations to the next stage.
