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About This Role
Job Description
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The Iowa Department of Revenue’s Internal Services Division is seeking a Data Scientist 1 to join the Data Analytics Bureau. The Internal Services Division plays a crucial role in ensuring the Department's day\-to\-day operations run smoothly, efficiently, and effectively. Its responsibilities span many areas, from the safeguarding of confidential taxpayer data, management of the GovConnectIowa Program, integration of technology solutions with business objectives, human resources, data analytics, and business continuity activities. The dedicated staff of this division focus on elevating both the internal and external customer experience. Throughout the year, the division coordinates education and outreach initiatives, fostering connection with our customers.
The Data Scientist will harness the Department’s incredible wealth of data to develop analytical insights, drive positive organizational value and outcomes to encourage the adoption of data driven decisions that will lead to improvements for the overall public good and IDR’s operations and performance.
In this position you will be responsible for:
- Working with stakeholders to identify opportunities to enhance the Department’s performance by using data\-driven tools to obtain, measure and analyze results.
- Conducting data analysis to uncover patterns, trends, and anomalies using statistical techniques (e.g. Heat Maps, Predicator Screening, Regression models, Time Series Models, Decision Trees Analysis, and Survey \& Text Analysis).
- Overseeing the identification, research, and investigation of opportunities for both leveraging data and adopting/applying new technology (e.g. artificial intelligence) to drive business growth, efficiency, and innovation.
- Researching and implementing techniques and tools in machine learning and artificial intelligence to make data analysis more efficient.
- Managing, implementing and maintaining the Analytical and Artificial Intelligence (AI) platforms used by the Department.
- Spearheading the Department’s usage of the Analytical and Artificial Intelligence platforms through dashboard development and maintenance of the platforms. This includes the technical support to improve the design of the models to run more efficiently.
- Developing, refining, and optimizing AI\-generated text prompts that are fed into AI platforms to ensure they are accurate, engaging, and relevant for various applications.
- Collaborating with different teams to improve the prompt generation process and overall AI system performance.
- Determining the data needed for key performance indicators (KPIs), metrics, and dashboards, gather the data from multiple sources, manipulate in preparation for analysis and present data findings and recommendations to stakeholders.
- Assisting in the building and design of statistical models (i.e. What\-if, Diagnostic, financial models) to answer business questions.
Preference will be given to candidates with experience in the following:
- Knowledge and experience using SAS Viya, Excel, SQL, and other analytical tools to respond to data requests and to solve problems. This consists of writing relevant code or reviewing existing code to resolve programming and data issues. It involves calculating, organizing, and summarizing data for analysis.
- Experience creating advanced visualizations and dashboards that clearly and easily communicate complex findings while adhering to industry best practices. This is done via the use of tools such as Tableau, Power BI, SAS Visual Analytics, JMP, etc.
- Experience in the management and administration of Analytical and Artificial Intelligence platforms
Job Specific Competencies:
- Mathematical Reasoning \- Choose the right mathematical methods or formulas to solve a problem.
- Critical Thinking \- Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
- Written Expression \- Communicate information and ideas in writing so others will understand.
Employer Highlights:
The Iowa Department of Revenue is a well\-respected employer. We are focused on providing excellent customer service, while offering a wonderful team atmosphere, work\-life balance, free parking, and casual attire. We offer a flexible working environment and opportunities to work from home with the ability to work from anywhere in the State of Iowa as long as it is your primary residence.
We have a great total compensation package for all of our full\-time employees, including:* Iowa Public Employees' Retirement System (IPERS)
- Retirement Investors Club (RIC)
- Flexible Working Environment\- Work from Home Opportunities
- Health, Dental and Vision Insurance
- Vacation Leave
- Sick Leave
- Paid Holidays (9 days/year)
- Flexible Spending Accounts
- Life Insurance
- Long\-Term Disability Insurance
The mission of the Iowa Department of Revenue is to serve Iowans through the responsible collection and generation of revenue to support the public good. If you’re looking for a career with an organization that values its employees and customers, you’ve come to the right place.
Applicants must live within the State of Iowa to qualify for this position.
This position will be required to come into the Hoover Building in Des Moines for meetings as needed.
Applicants must be legally authorized to work in the U.S. without the need for employer sponsorship, now or in the future.
A background check, including a criminal history check, fingerprint and Iowa tax filing check, will be conducted on the final candidate.
Effective July 1st, 2025, all Department of Revenue staff and their household will not be able to play any Iowa Lottery games.
E\-Verify and Right to Work
The State of Iowa participates in E\-Verify, a federal program that helps employers confirm the employment eligibility of all newly hired employees. Within the required timeframe, new hires will be verified through the E\-Verify system to ensure authorization to work in the United States. The State of Iowa also complies with the federal Right to Work laws, which protect employees’ rights to work without being required to join a labor organization. For more information, please visit www.e\-verify.gov
Minimum Qualification Requirements
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Applicants must meet at least one of the following minimum requirements to qualify for positions in this job classification:
NOTE: Unofficial Transcripts are required to verify degree and coursework
1\) Seven years of full\-time work experience in business/data/statistical analytics, economic research, or data science.
2\) Graduation from an accredited four\-year college or university with a degree in business analytics, economics, data science, statistics, mathematics, management information systems, or industrial management, and experience equal to three years of full\-time (as described in number one). NOTE: Only degrees listed are valid. NOTE: Unofficial Transcripts are required to verify degree and coursework
3\) All of the following (a, b, and c):
a. One year of full\-time work experience in business/data/statistical analytics, economic research, or data science; and
b. A total of four years of education and/or full\-time experience (as described in part a), where thirty semester hours of accredited college or university coursework in business analytics, economics, data science, statistics, mathematics, management information systems, or industrial management equals one year of full\-time experience; and
c. A total of two years of graduate\-level education and/or full\-time experience (as described in part a), where twenty\-four semester hours of accredited graduate college or university coursework in business analytics, economics, data science, statistics, mathematics, management information systems, or industrial management equals one year of full\-time experience. NOTE: Unofficial Transcripts are required to verify degree and coursework
4\) All of the following (a, b, and c):
a. One year of full\-time work experience business/data/statistical analytics, economic research, or data science; and
b. A total of four years of education and/or full\-time experience (as described in part a), where thirty semester hours of accredited college or university coursework in any field equals one year of full\-time experience; and
c. Graduation from an accredited college or university with a Master’s degree in business analytics, economics, data science, statistics, mathematics, management information systems, or industrial management. NOTE: Unofficial Transcripts are required to verify degree and coursework
5\) All of the following (a, b, and c):
a. Three years of full\-time work experience in business/data/statistical analytics, economic research, or data science; and
b. A total of four years of education and/or full\-time experience (as described in part a), where thirty semester hours of accredited college or university coursework in any field equals one year of full\-time experience; and
c. Possession of a professional certificate in data science, business analytics, or data analytics. NOTE: Copies of the certificate are required
6\) Current, continuous experience in the state executive branch that includes six months of full\-time work as a Data Analyst 2\.
For additional information, please click on this link to view the job description (Download PDF reader).
Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At State of Iowa, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $198,000 based on 808 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
State of Iowa AI Hiring
State of Iowa has 1 open AI role right now. They're hiring across Data Scientist. Based in Des Moines, IA, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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