DICK'S Sporting Goods, Inc. is hiring a Senior Data Scientist - Customer Intent, Decision Engine to lead the creation of intelligent systems that model customer intent and resolve identity dynamically. You'll design hybrid models combining behavioral prediction with causal reasoning to personalize experiences across search, fulfillment, and digital commerce, influencing the enterprise decisioning landscape.
What You'll Do
- Design and implement large-scale decision engines that dynamically resolve customer identity and intent in real time.
- Develop optimization frameworks like multi-armed bandits, reinforcement learning, and constrained optimization to balance personalization, business KPIs, and operational constraints.
- Build session-based and sequence-aware models using transformers, RNNs, and temporal point processes to capture evolving customer intent.
- Incorporate multimodal signals such as clickstream, search queries, transaction history, and CRM attributes into unified intent prediction pipelines.
- Deploy models with low-latency inference for real-time decisioning at scale.
- Define rigorous evaluation metrics including precision/recall for identity resolution, uplift for causal models, and latency for decision engines.
- Lead online experimentation like A/B tests and multi-cell experiments to validate model impact on personalization, conversion, and customer experience.
- Apply counterfactual evaluation techniques to measure the 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 like personalization, fraud prevention, and customer support.
- Communicate model performance to technical and non-technical audiences.
- 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.
What We're Looking For
- Bachelor's Degree or equivalent level preferred.
- Over 3 to 6 years of general professional experience.
- 4 to 6 months of basic managerial experience coordinating the work of others.
Nice to Have
- Advanced degree (MS/PhD) in Computer Science, Statistics, Applied Mathematics or a related field.
- 4+ years of experience in data science, machine learning, or AI with a track record of delivering production systems.
- Strong proficiency in hybrid modeling techniques: Machine Learning (deep learning, sequence models, transformers, recommender systems), Simulation and Mathematical Programming (MIP, agent simulation, LP), Causal Inference (treatment effect estimation, counterfactual reasoning).
- Experience building real-time recommendation systems that adapt to evolving customer behavior and context, using session-based modeling, embeddings, and reinforcement learning.
- Solid understanding of distributed systems, APIs, and cloud infrastructure like Azure, AWS, or GCP.
- Familiarity with reinforcement learning or contextual bandits for adaptive decisioning in dynamic environments.
- Familiarity with enterprise orchestration layers, integrating models into backend systems that power search, fulfillment, customer support, and personalization.
- Skilled in designing and analyzing A/B tests.
- Experience in an Agile working environment and at least one related project management tool such as Azure DevOps or Jira.
- Comfortable presenting results to cross-functional partners and helping them understand technical trade-offs.
- Collaborative, problem solving, and growth mindset with a strong focus on delivery.
- Prior work in eCommerce, retail, or customer identity resolution.
- Experience with synthetic data generation or simulation frameworks for intent modeling.
- Knowledge of optimization modeling including decision trees, bandits, and reinforcement learning for personalization.
Technical Stack
- Machine Learning: deep learning, sequence models, transformers, recommender systems
- Simulation and Mathematical Programming: MIP, agent simulation, LP
- Causal Inference: treatment effect estimation, counterfactual reasoning
- Distributed systems, APIs, Cloud infrastructure (Azure, AWS, or GCP)
- Reinforcement learning, Contextual bandits
- Enterprise orchestration layers
- Agile project management tools (Azure DevOps, Jira)
Team & Environment
You will join a high-performing team of ML Engineers and Scientists.
Benefits & Compensation
- Salary range: $83,000 - $138,200
- Competitive total rewards package including incentive, equity and benefits
- Compliance with all state paid leave requirements
- Generous suite of benefits
Work Mode
This is a global, remote position.
DICK'S Sporting Goods believes in how positively sports can change lives and is committed to creating an inclusive and diverse workforce, reflecting the communities we serve.
