This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re looking for a Data Scientist IV to join an innovative team collaborating with partners throughout the business to solve challenging problems. In this role, you’ll be optimizing company performance with algorithms, experimentation, and interactive dashboards. You will also have the opportunity to contribute to novel research studies and production-grade algorithms that serve students and educators. This position sits on the Data and AI team, a team that sets the standard for data-driven and scientific decision-making throughout the business. The ideal candidate is a creative problem solver with excellent technical and communication skills and is committed to fostering a culture of continuous learning and innovation. What You'll Do - Lead the Development and Optimization of Machine Learning Models: Spearhead the design, development, and optimization of advanced machine learning models to personalize learning experiences, predict student outcomes, and enhance educational content delivery. - Data Analysis and Insight Generation: Utilize statistical analysis and data mining techniques to analyze vast amounts of data, deriving actionable insights that inform product development, user engagement strategies, and educational content improvement. - Collaborate on Cross-Functional Projects: Work closely with product managers, software engineers, and educational specialists to integrate data science solutions into the platform, ensuring they meet the company's educational goals and user needs. - Mentor and guide junior data scientists and analysts, fostering a culture of learning and continuous improvement within the team. - Regularly interact with senior management or executive levels in matters concerning data science. - Keep abreast of the latest developments in data science, machine learning, generative AI, and education technology, applying new techniques and technologies to solve complex problems in the educational domain. - Ensure the ethical use of data, adhere to privacy laws and regulations, and implement best practices in data governance to protect sensitive information related to students and educators. Qualifications - Advanced education (PhD or Master’s) in a quantitative field (science, math, statistics, engineering, etc.) with professional work experience as a Data Scientist. - 7+ years of experience leading data science initiatives to deliver impactful results. - Excellent written and oral communication skills. - An outstanding ability to communicate complex findings to stakeholders outside of Data Science in a clear, simple, and concise manner. - Prior experience mentoring and supporting junior to mid-level data scientists. - Advanced skills in Python, SQL. - 7+ years of experience with Natural Language Processing and Deep Learning. - Experience with git and cloud computing (AWS, GCP, or Azure). - Strong proficiency in traditional statistics and ML approaches. - Experience extracting data from a variety of sources in different formats. - Knowledge of best practices in coding/scientific projects. - Eager to take initiative in a fast-paced, ever-changing, dynamic environment. - Thrilled for the opportunity to truly impact the education landscape. Benefits - Competitive pay, complete health insurance, 401(k) matching, and an employee equity plan. - Flexible time off, 13 paid holidays, paid parental leave, and a paid year-end holiday break. - A robust catalog of benefits that support your professional growth and personal well-being: wellness days, work-from-home funds, fertility & adoption reimbursement, and more… - A varied and challenging role in an innovative, global company. - Supportive, driven colleagues who have your back and share your passion.

• Leading the design and implementation of advanced data science methodologies and statistical models to support clinical research and data analysis. • Guiding a team of data scientists and analysts in the development and execution of data-driven strategies to optimize clinical trial design and outcomes. • Collaborating with cross-functional teams, including clinical, biostatistical, and regulatory experts, to ensure integration of data science insights into clinical development programs. • Driving innovation in the use of data science tools and techniques, including machine learning and predictive analytics, to enhance the efficiency and effectiveness of clinical trials. • Providing strategic direction and oversight for data management and analysis processes, ensuring compliance with regulatory requirements and industry best practices. • Communicating complex data findings and insights to stakeholders, including senior leadership and external partners, to support decision-making and strategic planning.

• Supporting the development and improvement of machine learning models used in sustainability analytics • Cleaning, processing, and transforming large structured and unstructured datasets • Conducting exploratory data analysis to identify trends, patterns, and anomalies in ESG and sustainability data • Assisting in building data pipelines and analytical workflows to improve data quality and efficiency • Collaborating with data scientists and engineers to test and evaluate model performance • Creating visualizations and summaries to communicate analytical findings clearly • Contributing to documentation and internal tools that improve data accessibility and reproducibility

• Design, develop, and maintain risk models using advanced machine learning techniques, including hybrid and sequential approaches. • Regularly retrain, monitor, and validate existing models to ensure timely adaptation to changing customer behavior. • Build and manage scalable data marts in BigQuery to support model development and analytical needs. • Contribute to development of internal automation tools (e.g., AutoML components, ML workflows). • Provide data-driven insights through ad-hoc analyses to support product, credit, and operations teams. • Participate in early research and prototyping of new architectures (Transformers, foundation-style embeddings, multimodal models).