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About This Role
At ACT, Your Work Makes a Difference
Education has power – a power that changes lives forever. It creates opportunities that lift up individuals, their families, and sparks societal change that echoes through generations to come. From our grassroots we have fought the good fight for equity in education, and we remain devoted to helping anyone who struggles to access that power. This is what matters to us and we must do better - we’ve never been more sure of our purpose.
ACT team members are part of an organization dedicated to a mission that has never been more important: Helping people achieve education and workplace success. Advancing that mission within our organization, by helping our team members achieve education and workplace success of their own, is core to our values. ACT values a diverse workplace and is committed to fostering an inclusive, equitable environment in which every team member has an opportunity to grow.
We want our team members to have the well-being and confidence they need to do their best work, in an environment where both they and ACT thrive. To support this, our total rewards include company paid life insurance, medical, dental, vision, flexible health and dependent spending accounts, 401(k) retirement savings with company match, paid holidays, paid time off, and so much more. You can find a comprehensive list of our benefits here.
We are seeking a Data Scientist II to help us fulfill that mission.
ACT is seeking a Data Scientist II to help build a new pathway navigation experience that helps high school students explore, plan, and take confident next steps toward college and career. This role will design, test, and validate the data models that power personalized college, career, and pathway recommendations. You will work cross-functionally with product, engineering, research, design, and business partners to combine student, education, assessment, interest, skills, and career data into relevant, explainable, and actionable recommendations. You will move quickly from early experimentation to production implementation while ensuring that models are accurate, transparent, fair, and appropriate for use with students and families.
The finalist will be hired at the salary and level commensurate with their qualifications. For this position, we anticipate offering an annual salary in the range of $95,000 to $105,000. ACT manages salaries within the range based on relevant factors including, skills, experience, and internal equity.
Location: This is a remote position, based in the United States.
Visa: Applicants must be authorized to work in the U.S. without the need for visa sponsorship.
Please Note: This is a Fixed Term Position that will last 6 months, with the possibility of an extension or conversion to a fulltime position.
What you will be working on:
Data Science and AI Development:
- Design, prototype, and evaluate models that generate personalized college, career, and pathway recommendations
- Apply statistical modeling, machine learning, and generative AI to rapidly test and improve product capabilities
- Evaluate model performance, fairness, bias, and appropriate use
Product Data and Experimentation:
- Design data collection strategies that capture student behavior, performance, and engagement while supporting rapid product development
- Analyze pilot and user-study data and translate findings into actionable product recommendations
- Define metrics and experiments to evaluate recommendation quality and product impact
Data Architecture and Production:
- Partner with engineers to build scalable cloud-based data pipelines and move models from prototype into production
- Integrate data from student, education, assessment, skills, career, and labor-market sources
- Establish reliable processes for data security, model documentation, deployment, monitoring, and maintenance
Student-Centered Personalization:
- Develop approaches that produce useful recommendations when student data is incomplete and adapt as new information becomes available
- Use behavioral and performance data to support personalized and adaptive product experiences
- Make model outputs understandable and actionable for various stakeholders
Cross-Organizational Collaboration:
- Collaborate across teams to align data, modeling, research, and product requirements
- Translate research and business needs into data collection plans and technical solutions
- Communicate analytical findings, assumptions, risks, and tradeoffs to technical and nontechnical stakeholders
This could be the job for you if you have (minimum requirements):
- Bachelor’s degree in data science, computer science, statistics, applied mathematics, economics, operations research, or a related quantitative discipline, or equivalent combination of education and experience.
- At least 3 years of applied data science experience, including building statistical or machine-learning models and analyzing product experiments, pilots, or user studies
- Proficiency in Python and SQL, with experience developing scalable data pipelines and moving data products or models from prototype toward production
Knowledge, Skills and Abilities:
- A hands-on, product-oriented data scientist who can move from analysis and rapid prototyping to production implementation
- Strong in statistical modeling, machine learning, experimental design, and model evaluation
- Experienced in scalable data pipelines, cloud environments, and integrating complex data sources
- Skilled at using behavioral and performance data to develop personalized product experiences
- Thoughtful about responsible AI, including fairness, bias mitigation, transparency, privacy, and appropriate use
- An effective cross-functional communicator who translates research and business needs into actionable technical solutions
It’s a plus if you have (preferred requirements):
- Master’s degree in data science or related field
- Experience with recommender systems, generative AI, natural language processing, or personalized and adaptive systems
- Experience with education, assessment, career, workforce, labor-market, occupational, or skills data
About ACT
When ACT was founded in 1959, it disrupted the assessment industry with a new approach to helping students better understand their readiness so they could take steps to improve it. By leveraging our expertise and authority in assessment and research, we will again disrupt the industry—helping more people learn, better measure their progress, and improve their navigation through life’s transitions.
More than ever before, ACT is fulfilling its mission of helping people achieve education and workplace success. We’re doing it by pushing the boundaries of learning innovation through the work of our people, who we call team members because we’re all in this together.
We know transformation does not come without challenge. That’s why ACT invests in a variety of experiences for team members to strengthen their connections, explore ideas, learn from customers, and celebrate success.
Learn more about working at ACT at act.org!
ACT is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. ACT participates in E-verify. ACT's online position announcements are intended only to provide general descriptions of employment opportunities; none of the information provided for any position should be interpreted as a commitment by ACT to specific terms and conditions for employment.
Completion of the ACT National Career Readiness Certificate is recommended. Find a testing site near you to register for the WorkKeys assessments. Finalists for this position will be subject to a criminal background check as a condition of employment.
*If you have received an ACT employment-related communication from an email address that is not affiliated with @act.org and/or that requests personal or financial information, please do not reply. Instead, reach out to us at [email protected] with the details. ACT's recruitment team appreciates your interest in working with us to transform college and career readiness pathways for all learners and wishes you the best of luck in your career journey.*
Salary Context
This $95K-$105K range is in the lower quartile for Data Scientist roles in our dataset (median: $161K across 138 roles with salary data).
View full Data Scientist salary data →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 9,079 AI roles we're tracking, Data Scientist positions make up 4% of the market. At ACT, 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 $190,000 based on 1,503 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($100K) sits 47% below the category median. Disclosed range: $95K to $105K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
ACT AI Hiring
ACT has 1 open AI role right now. They're hiring across Data Scientist. Based in Iowa City, IA, US. Compensation range: $105K - $105K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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.
Frequently Asked Questions
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