Senior Manager, Applied AI, Data Science

This is a fully remote position, open to applicants in Pennsylvania.

📋 Description

• Collaborate with business leaders to identify, define, and prioritize opportunities in AI, data science, and advanced analytics.

• Develop, validate, and maintain predictive models, including solutions for propensity, segmentation, lead-scoring, and next-best-action.

• Create AI agents, copilots, and intelligent workflows to minimize manual efforts and enhance knowledge-intensive business processes.

• Design lead-generation and customer analytics solutions utilizing transaction, behavioral, demographic, and other pertinent data.

• Convert ambiguous business inquiries into analytical strategies, requirements, success metrics, and implementation plans.

• Facilitate discovery sessions, communicate insights, and present recommendations to both technical and non-technical stakeholders.

• Assess and pilot emerging AI, machine learning, and analytics tools, platforms, and vendor capabilities.

• Collaborate with Technology, Information Security, Risk Management, Compliance, and other stakeholders to ensure secure, responsible, and compliant deployment.

• Establish standardized practices for documentation, testing, performance monitoring, and ongoing enhancement of models or solutions.

• Provide mentorship to analysts and data scientists, enhancing AI and analytics capabilities throughout the organization.

⛳️ Requirements

• A Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or a related quantitative field is mandatory.

• At least seven years of progressively responsible experience in data science, machine learning, advanced analytics, or applied AI.

• Proficiency in predictive modeling, machine learning, statistical analysis, segmentation, and model evaluation techniques.

• Familiarity with generative AI, large language models, AI agents, and workflow automation concepts.

• Proficient in Python and SQL; experience with R or similar analytical languages is advantageous.

• Knowledge of model development, deployment, monitoring, documentation, and MLOps practices.

• Understanding of data governance, model risk management, responsible AI, and information security principles.

• Experience with customer analytics, lead generation, campaign measurement, and test-and-learn methodologies.

• Ability to align business strategy and operational challenges with practical AI and analytics solutions.

• Capability to work independently across the entire solution lifecycle, from discovery and prototyping to implementation and monitoring.

• Skill in articulating complex technical concepts clearly to business leaders and translating stakeholder needs into technical requirements.

• Ability to influence priorities and cultivate trusted partnerships across business, technology, risk, and control functions.

• Competence in balancing innovation, speed, feasibility, explainability, and risk within a regulated environment.

• Ability to manage multiple initiatives, navigate ambiguity, and focus efforts on measurable business outcomes.

• Capability to mentor others and contribute to a collaborative, solutions-driven team culture.

• Proven experience in developing and implementing predictive models and data-driven business solutions.

🏝️ Benefits

• Performance-based bonuses or incentives.

• 401(k) matching.

• Profit sharing opportunities.

• Employee stock purchase plan.

• Paid time off.

• Medical insurance coverage.

• Dental insurance coverage.

• Vision insurance coverage.

• Company-paid life insurance.

• Long-term disability insurance.

• Supplemental voluntary life insurance.

• Short-term disability insurance.

• Wellness incentives.

• Employee assistance program.

• Pre-tax health savings accounts.

• Flexible spending accounts.