Data Scientist II

ACT Education•Iowa City, IA
•Remote

About The Position

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. This is a remote position, based in the United States. Applicants must be authorized to work in the U.S. without the need for visa sponsorship. This is a Fixed Term Position that will last 6 months, with the possibility of an extension or conversion to a fulltime position.

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
  • 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

Nice To Haves

  • 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

Responsibilities

  • 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
  • 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
  • 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
  • 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
  • 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

Benefits

  • 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
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