Research, design, develop, and test Pearson’s bedrock learner model to power the next generation of pan-business unit AI-driven learning products
Partner with Product, Engineering, and Design teams to define and implement AI strategies across higher education courseware and direct to consumer learning products
Design, develop, and maintain a scalable AI data and delivery architecture to deliver real-time personalized features including proficiency estimates and recommendations upon which we build the future of learning from Pearson
Using this architecture, develop the customer-facing AI capabilities with which Pearson can re-invent our courseware business for the AI age
Test and iterate quickly without sacrificing quality (0 to go-to-market in <6months)
Translate product opportunities into clear data requirements
Build prototypes, articles, and presentations to educate the organization (including senior executives) on the latest AI innovations and how we will turn them into business growth
Publish and patent new math, data, and AI inventions
Collaborate with Data Engineering to ensure clean, reliable data pipelines and seamless front-end delivery
Evangelize a data-informed culture across Product and Engineering teams through education, enablement, and scalable tooling
Monitor data quality and tracking integrity, proactively identifying and resolving gaps or anomalies
Be undaunted by urgency and ambiguity and be persistent in defining requirements and creative in designing solutions.
Wrangle and clean data as needed.
Support fellow data analysts, data scientists, and engineers to solve data problems, solve customer and product problems with data, govern quality data, and connect data problems with technical solutions.

Requirements

5 years developing AI/ML capabilities, including 3+ years in delivering AI/ML for learning
Expertise in the mathematical foundations of statistics, machine learning, numerical optimization, economics, analytics, econometric and psychometric modeling, recommendation systems, and natural language processing
Degree in analytical or related science, including PhD (or candidate) in AI/ML Machine Learning
Experience designing and developing AI/ML testing, training, deployment, and maintenance/CI/CD/CT architecture and pipelines
Ability to interpret business goals and translate them into technical solutions
Proficient at making complex data and mathematical concepts understandable with all levels of product teams and engineering teams
Persistence in creative problem solving, organization, and time management
Experience turning research into quick execution that drives business growth
Experience working very closely with cross-functional product teams and building strong relationships
Strong background in machine learning, including Bayesian methods, natural language processing, and recommendation systems, using tools such as Pandas, NumPy, SciPy, TensorFlow, PyTorch, and NLP libraries like Hugging Face Transformers and spaCy.
Proficient in Python, SQL, and Bash/Shell scripting.
Effectively communicate technical concepts to non-technical audiences and represent non-technical concepts to technical audiences
Preferred - experience deploying containerized workflows using GitLab CI/CD, Docker, ECS or Kubernetes, and managing cloud infrastructure via AWS CLI and Terraform a plus.
Preferred - experienced in building scalable MLOps pipelines for data ingestion, preprocessing, training, and deployment, with orchestration using Airflow and experiment tracking via MLflow a plus.

Benefits

Eligible to participate in an annual incentive program

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI/ML capabilitiesmachine learningnatural language processingrecommendation systemsdata cleaningdata pipelinesCI/CD architecturemathematical foundations of statisticsnumerical optimizationeconometric modeling

Soft Skills

creative problem solvingorganizationtime managementcommunicationcollaborationpersistencetranslating business goalseducating teamsbuilding relationshipsinterpreting technical solutions

Certifications

PhD in AI/ML Machine Learning