Master's degree in a quantitative field (Statistics, Data Science, etc.)
Minimum of 7 years of experience in data science, machine learning, and AI
Expertise in applied AI, particularly generative AI and large language models
Proficiency in data science toolkits (Python, R, TensorFlow, etc.)
Strong applied statistics skills and familiarity with relational/NoSQL databases
Responsibilities
Implement AI strategy to enhance data readiness and drive AI adoption
Design large language model-based tools for user-friendly data access
Build and refresh machine learning models, applying best engineering practices
Translate business requirements into analytical problem statements
Collaborate with cross-functional teams to integrate data science capabilities
Benefits
Health, dental, and vision insurance
Company paid life insurance
401(k) with company match
Paid time off and parental leave
Employee assistance program
Wellness programs like Headspace
Charitable matching program
Full Job Description
WHAT YOU'LL DO
The Senior Data and AI Scientist leads strategic data science and AI initiatives across Ascend Learning, driving AI adoption and improving enterprise data readiness for AI and machine learning use cases. This role designs and implements advanced analytical and AI/LLM-based solutions - including generative AI and conversational data-access tools - that span multiple business functions, translating complex business needs into scalable, high-value data science and AI solutions.
WHERE YOU'LL WORK
You will work a hybrid schedule from our Leawood, KS or will consider remote within the United States
HOW YOU'LL SPEND YOUR TIME
Implement enterprise data AI strategy to drive data-readiness, and enable AI adoption: identify and evaluate opportunities to apply artificial intelligence and generative AI data analytics across the organization, and assess and improve the quality, structure, and governance of enterprise data so it is fit for AI and machine learning use.
Design and build large language model-based tools and interfaces (e.g., Claude) that let business users and internal platforms query and act on organizational data using natural language, increasing AI adoption and self-service access to data-driven insights.
Design, build, and refresh machine learning and AI models: conduct experiments and proof-of-concept research, prepare data, and develop the underlying data models and databases needed to support new and existing business initiatives, applying disciplined engineering practices such as version control, automated testing, and documentation to ensure reliable, reproducible solutions.
Convert business questions into analytical solutions: translate business needs into clearly defined analytics problem statements, interpret results using techniques ranging from simple data aggregation to complex data mining, and apply data science methods to support functions such as sales targeting, so business partners can make informed, data-driven decisions.
Partner with leadership and technical teams across the organization: collaborate with Engineering, Data, and Operations teams to embed data science and AI capabilities into products and workflows, and work directly with business leaders and end-users from concept through delivery to understand business trends, needs, and problems.
WHAT YOU'LL NEED
Education & Years of Experience
Master's degree in Statistics, Data Science, Computer Science, Mathematics, Operations Research, or a similar quantitative field.
A minimum of 7 years' experience working on data science, machine learning, and artificial intelligence projects in industry, with a strong and growing emphasis on applied AI and generative AI/large language model-based solutions.
Key Skills and Abilities/Qualifications
Deep, hands-on technical expertise across the full data science and applied AI stack.
Advanced proficiency with data science toolkits (e.g., Python NumPy, SciPy, Scikit-learn, TensorFlow, R, Spark ML, Azure ML), programming and scripting for reproducible analysis, and building classification, regression, clustering, and deep learning models.
Specialized knowledge of generative AI and large language model tooling and frameworks (e.g., retrieval-augmented generation, prompt engineering, vector embeddings), and hands-on experience defining semantic models and metadata within Snowflake so enterprise data is reliably consumable by both business users and AI systems.
Strong applied statistics skills, experience with both relational and NoSQL databases, and familiarity with data visualization tools.
Judgment to translate ambiguous business requirements into well-defined, high-value solutions.
Ability to do minimal travel, less than 10%.
HIRING RANGE
The current full-time, annualized base pay hiring range for this role is $151,000.00-$215,930.00. In accordance with applicable state laws, we are providing the expected pay range for this position. Individual compensation will be determined by various factors, including relevant experience, qualifications, current business needs and local market factors. Most regular, full-time employees are eligible to participate in an Ascend incentive bonus or sales plan.
BENEFITS
Health, dental, and vision insurance
Company paid life Insurance
401(k) with company match
Paid time off and parental leave
Employee assistance program
Other wellness programs such as Headspace and Airvet
Charitable matching program
About Ascend Learning
Ascend Learning is a leading provider of educational content, software and analytics solutions for healthcare and other vocational industries. The company's products and services are designed to help students and professionals improve their knowledge and skills, and to help employers improve their workforce performance. Ascend Learning's portfolio includes more than 1,000 digital and print-based products, including textbooks, online courses, simulation tools, and certification and licensure exam preparation materials. The company serves a wide range of customers, including colleges and universities, healthcare organizations, and government agencies. Ascend Learning was founded in 2010 and is headquartered in Woburn, Massachusetts.
