Professionals in predictive analytics have acquired the knowledge and technical skills to navigate the various in-demand jobs in the field of data science. From analysts to directors, jobs in this field are in high demand across many sectors and industries, which includes opportunities for both career growth and competitive compensation packages.

The demand for professionals in predictive analytics is due to the knowledge and skills required to be successful in this career path. Common among these dynamic professionals are a requirement of the following:

• Solid quantitative skills and an affinity for numbers
• The ability to code – Python, R, and SQL are essential in this industry
• Communication skills
• The ability to problem-solve and make decisions that fall outside the job description

As a result, salaries in this profession are very appealing to professionals, including entry-level salaries for analysts. According to the 2019 Burtch Works Study, median income for individual contributors is $80,000 at the low end and rise to over $130,000 at the higher end. For data scientists, including managers and directors, the median salary range is from $130,000 at the low end and up to approximately $250,000 at the high end. It is also important to note that salary increases from year to year has been consistent across all job categories, with increases of 3% at the low end up to 11% on the high end for managers.

A similar study by Robert Half in 2020 provides detailed breakdowns of salaries across job levels and across both Canada and the US, with adjustments by major city relative to the national average. The findings in this study are consistent with the Burtch study. It also shows that the generous compensation packages reflect more than salary, with many positions including health and dental insurance, paid time off, and a retirement savings plan. You will also find in this report a detailed list of roles that are in high demand, including the following:

• AI specialists (programmers, engineers)
• Blockchain developers and engineers
• Business intelligence analysts
• Cloud specialists (engineers, architects, systems engineers)
• Data specialists (engineers, scientists, visualization experts)
• Developers (web, software, mobile, VR/AR/MR)
• DevOps engineers
• Full-stack developers
• Help desk and desktop support professionals
• IoT specialists (architects, engineers)
• Machine learning specialists
• Network administrators

This study also shows that demand for these professionals go beyond financial services, with demand trending in the manufacturing, health care, and technology sectors. Hiring trends overall show demand across all industries with recruiters finding it difficult to find top candidates for open positions as most of these candidates are already employed.