Senior Data Scientist - Customer Intent, Decision Engine (REMOTE)

DICK'S Sporting Goods is a leading sports retailer committed to enhancing lives through sports. They are seeking a Senior Data Scientist to lead the development of intelligent decisioning systems that model customer intent and resolve identity dynamically in real time, directly influencing personalization and customer experience.

Responsibilities:

• Design and implement large-scale decision engines that dynamically resolve customer identity and intent in real time
• Develop optimization frameworks (multi-armed bandits, reinforcement learning, constrained optimization) to balance personalization, business KPIs, and operational constraints
• Build session-based and sequence-aware models (transformers, RNNs, temporal point processes) to capture evolving customer intent
• Incorporate multimodal signals (clickstream, search queries, transaction history, CRM attributes) into unified intent prediction pipelines
• Deploy models with low-latency inference for real-time decisioning at scale
• Define rigorous evaluation metrics (precision/recall for identity resolution, uplift for causal models, latency for decision engines)
• Lead online experimentation (A/B tests, multi-cell experiments) to validate model impact on personalization, conversion, and customer experience
• Apply counterfactual evaluation techniques to measure causal impact of identity decisions
• Translate technical insights into clear recommendations for product, marketing, and executive stakeholders
• Partner with product managers to align decision engine outputs with business objectives (e.g., personalization, fraud prevention, customer support)
• Communicate model performance to technical and non-technical audience
• Ensure models are production-ready with robust monitoring, retraining schedules, and A/B testing frameworks
• Implement feature stores and model registries to streamline experimentation and deployment

Requirements:

• Deep expertise in AI, Machine Learning, and Data Science
• Experience in traditional machine learning and cutting edge AI with a strong foundation in causal inference
• Ability to design hybrid models that combine behavioral prediction with causal reasoning
• Experience in solving complex decision problems using predictive analytics, causal modeling, simulation, and mathematical programming
• Ability to influence the enterprise decisioning landscape by developing models that integrate with high-impact systems
• Experience in collaborating with product, engineering, and business leaders
• Ability to translate ambiguous customer journeys into solvable data science problems
• Experience in defining rigorous evaluation metrics for identity resolution and causal models
• Experience in leading online experimentation to validate model impact
• Ability to communicate model performance to technical and non-technical audiences
• Experience in ensuring models are production-ready with robust monitoring and retraining schedules
• Experience in implementing feature stores and model registries
• Advanced degree (MS/PhD) in Computer Science, Statistics, Applied Mathematics or related field
• 4+ years of experience in data science, machine learning or AI with a track record delivering production systems
• Strong proficiency in hybrid modeling techniques
• Experience with deep learning, sequence models and transformers, recommender systems
• Experience with simulation and mathematical programming techniques
• Experience with causal inference techniques
• Experience building real-time recommendation systems
• Solid understanding of distributed systems, APIs, and cloud infrastructure (Azure, AWS, or GCP)
• Familiarity with reinforcement learning or contextual bandits
• Familiarity with enterprise orchestration layers
• Skilled in designing and analyzing A/B tests
• Experience in an Agile working environment and at least one related project management tool
• Comfortable presenting results to cross functional partners
• Prior work in eCommerce, retail, or customer identity resolution
• Experience with synthetic data generation or simulation frameworks for intent modeling
• Knowledge of optimization modeling techniques