Snr Lead Data Scientist

ADP is seeking a Senior Data Scientist dedicated to Global Payroll transformation priorities. This role will serve as a key decision intelligence resource, designing and building advanced analytics and applied AI solutions from structured and unstructured data, with an initial focus on customer intent analysis and a broader mandate over time across process analytics, task analytics, and other decision intelligence use cases.

Role Purpose

This role exists to strengthen decision intelligence capabilities for Global Payroll transformation by delivering scalable analytics and applied AI solutions that improve business decision making and operational performance. The role is intended for a senior hands-on technical builder who can develop reusable capabilities, operationalize advanced analytical methods, and extend decision intelligence across multiple transformation use cases.

Key Responsibilities

1. Design and build decision intelligence solutions
• Design, develop, and deploy advanced analytics and applied AI solutions for priority Global Payroll transformation use cases, beginning with customer intent analysis
• Apply machine learning, NLP, LLMs, embeddings, semantic search, and RAG-based methods to generate scalable decision-support capabilities from structured and unstructured data
• Build solutions that can evolve into broader process, task, and operational analytics applications across the Global Payroll domain
2. Develop reusable analytical models, workflows, and AI components
• Build reusable analytical methods and technical assets, including segmentation approaches, driver analysis, root cause frameworks, intent and theme detection pipelines, prompts, and model workflows
• Package code, workflows, and solution components for repeatable use across multiple transformation priorities
• Contribute to a scalable technical foundation for decision intelligence capability development

3. Operationalize and scale technical solutions

• Evaluate, monitor, and refine analytical models and AI solutions for accuracy, performance, scalability, and production readiness
• Collaborate with technical and data partners to align solutions with enterprise platforms, deployment practices, governance expectations, and data quality standards
• Support sustainable rollout of analytical and AI capabilities into business-facing decision support environments

4. Strengthen applied AI and advanced analytics capability

• Establish best practices for applied AI, advanced analytics development, experimentation, and technical quality
• Mentor analysts and analytics partners on advanced analytical thinking and practical AI application
• Help raise the maturity of decision intelligence capability through reusable methods, technical standards, and strong delivery discipline

Profile

Education

• Master’s degree in data science, Computer Science, Statistics, Applied Mathematics, Engineering, or another quantitative field
• Advanced degree preferred; equivalent practical experience in advanced analytics and AI delivery will also be considered

Experience

• 5+ years of experience in data science, machine learning, or advanced analytics roles, with strong hands-on delivery in production-oriented environments
• Experience applying advanced analytics and AI techniques to structured and unstructured data for business decision support
• Experience delivering reusable models, analytical assets, or AI-enabled capabilities in cross-functional, transformation-oriented environments
• Experience working with business and technical partners to support adoption of analytical solutions

Technical Skills

• Strong Python and SQL skills, with experience in modern data science and analytics workflows
• Hands-on experience with machine learning, NLP, LLMs, embeddings, semantic retrieval, RAG, and applied Generative AI frameworks
• Experience developing predictive models, segmentation, root cause analysis, driver analysis, and intent or theme detection approaches
• Familiarity with Databricks, Spark or PySpark, and production-oriented model or AI workflow deployment practices
• Experience with feature engineering, model evaluation, monitoring, and production-quality, version-controlled analytical code

Behavioral Competencies

• Strong technical problem-solving and solution design capability
• Clear communicator across technical and non-technical audiences
• Ability to connect analytical work to business impact without drifting into purely business-analysis ownership
• Ownership mindset with a balance of innovation, execution, and scalability