Though data scientists are widely recognized for the contributions to areas like finance, healthcare, logistics and more, they have been essential to public works projects in South Dakota and are being compensated accordingly.
The South Dakota Department of Transportation applied for funding in 2013 to analyze rural state and local highways with predictive modeling techniques to reduce the likelihood of traffic accidents. This proposed project could greatly impact South Dakota’s ability to allocate public safety funding from the federal government without additional limitations being imposed.
The federal Highway Safety Manual recommends several predictive methods. Safety Performance Functions (SPF) predict the number of accidents at a location based on the characteristics of the site and its traffic volume. An additional type of predictive modeling uses Crash Modification Factors (CMF), which predict the number of crashes at a site after a safety improvement has been implemented. Using these models can identify sites that have a higher number of actual crashes than what was predicted. Such sites may need modifications to improve their safety.
However, not all of South Dakota’s highways have the geographic characteristics of those used in these predictive models. For instance, many of the state’s highways have a low volume of traffic. Also, they may not meet the base conditions assumed by an SPF or CMF such as having a minimum shoulder width of 6 feet and a minimum roadway width of 12 feet. The South Dakota Department of Transportation plans on calibrating the SPFs to South Dakota’s conditions, so they can improve the safety of the state’s highways.
Salary Ranges for Data Scientists in South Dakota’s Biggest Cities
South Dakota strongly advocates increasing the role of technology in the state’s business climate. The South Dakota Experimental Program to Stimulate Competitive Research partnered with Forward Sioux Falls to make the state a hub for tech development in the coming years. In fact, the website Techie.com featured Sioux Falls as one of the most promising tech hubs of 2014. This area is considered part of “Silicon Prairie.”
With the number of high powered banks located in South Dakota and particularly in Sioux Falls, banking technology such as credit card security is big business in the state.
In recent years, South Dakota’s liberal banking laws led to a focus on creating trusts for wealthy individuals. Sioux Falls is home to more than 50 trust companies according to the Federal Reserve Bank of Minneapolis. Even Pierre with its population of 13,000 has nine trust firms.
Thus, data scientists in both Pierre and Sioux Falls earned higher starting salaries than their colleagues in other cities in South Dakota as of 2016 according to the tech staffing firm Robert Half Technology. This company places thousands of jobseekers throughout the country each year and accumulates highly accurate data on the starting salaries of tech workers. These salary figures do not include relocation assistance or bonuses.
Relocation assistance is common in corporate America these days. As of 2011, the 45th Annual Corporate Relocation Survey from Atlas Van Lines indicated that 65% of the firms surveyed offered full reimbursement for relocated employees. With the increasing levels of demand for data scientists, this figure is likely to be even higher at this time.
Robert Half draws from US Bureau of Labor Statistics research to account for geographic variation throughout South Dakota and provides up-to-date salary expectations for data scientists in the state:
- Pierre: $97,000 – $137,000
- Sioux Falls: $91,000 – $129,000
- Sioux City: $82,000 – $116,000
- Rapid City: $79,000 – $112,000
Salaries for Data Scientists in South Dakota According to Industry and Area of Specialty
According to the South Dakota Department of Labor and Regulation, data scientist working as statistical modeling specialists with salaries that fell within the 90th percentile earned an average of more than $92,000 a year as of 2015. Data scientists working in the area of operations research earned even higher salaries with those in the 90th percentile earning an average salary in excess of $146,000:
Operations Research
- $146,722
Statistical Modeling Specialist
- $92,569
The US Department of Labor, Bureau of Labor Statistics information shown here reflects salary data for broad occupational classifications that include data scientists. These estimates are expressed as the 90th percentile average to reflect the fact that data scientists are recognized as the top earners within each classification.