Lennar
About Lennar
Lennar is one of the nation's leading homebuilders, a Fortune 500® company recognized for building quality homes and providing exceptional customer service while fostering an opportunity‑rich culture for associates.
Role Overview Senior Data Scientist – responsible for designing, building, and deploying advanced AI models and autonomous agents to shape pricing, sales, and personalization across 40+ divisions.
Responsibilities
Design, build, and deploy autonomous AI agents using Amazon Bedrock, AgentCore, and related frameworks.
Apply machine‑vision and feature‑extraction techniques to home attributes (photos, plans, finishes) for premium pricing and personalization.
Engineer and maintain scalable data pipelines and systems that support all models and agents.
Integrate agents with enterprise systems and protocols (MCP servers, A2A, internal APIs).
Design and run experiments (A/B tests, multi‑armed bandits, uplift models) to optimize performance.
Ensure observability and reliability of deployed agents (logging, evaluation, monitoring, drift detection).
Gather stakeholder feedback and adapt solutions for adoption and measurable impact.
Translate complex data‑science concepts into clear recommendations, stories, and visualizations for executives and non‑technical audiences.
Favor incremental, explainable solutions that deliver quick wins and scale over time.
Drive experimentation with new tools and approaches, ensuring robustness, governance, and scalability in production deployments.
Share learnings with the broader team to raise the bar on data‑science and agent‑centric development.
Manage timelines and expectations transparently with the data‑science team and business stakeholders.
Requirements
Bachelor’s or Master’s degree in Statistics, Economics, Math, Computer Science, Data Science, Machine Learning, or related field (or equivalent experience).
5+ years of relevant experience (1+ with PhD, 3+ with MS) in data science, ML engineering, or applied AI development delivering production‑ready models and systems.
Strong proficiency in Python and SQL, owning the full data‑science stack (data pipelines + models + deployment).
Hands‑on experience with AI development frameworks (LangChain, Strands, Amazon Bedrock, AgentCore, or equivalent).
Experience with experimentation frameworks (A/B testing, uplift modeling, multi‑armed bandits, causal ML).
Exposure to machine‑vision techniques (CNNs, transfer learning, embeddings) and NLP techniques (embeddings, transformers, prompt engineering).
Understanding of AI agent observability (evaluation frameworks like LangFuse, RAGAS, Weights & Biases, custom monitoring).
Experience with system integrations: APIs, A2A protocol, MCP servers, orchestration pipelines.
Comfort working with large‑scale, imperfect real‑world datasets and making progress despite complexity.
Strong engineering skills: design and maintain production pipelines, microservices, and scalable systems.
Proven ability to navigate ambiguity, rapidly prototype, and move solutions into production.
Collaborative communicator who can align technical solutions with business priorities across diverse stakeholders.
Bonus: experience with RAG pipelines, LLM fine‑tuning, RLHF, multi‑agent orchestration, feature stores, survival analysis/churn modeling, and attribution modeling.
Physical & Office Requirements Primarily a sedentary office position. Requires ability to operate computer equipment, speak, hear, bend, stoop, reach, lift, move, and carry up to 25 lbs. Finger dexterity necessary.
EEO Statement Lennar is an equal‑opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.
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Role Overview Senior Data Scientist – responsible for designing, building, and deploying advanced AI models and autonomous agents to shape pricing, sales, and personalization across 40+ divisions.
Responsibilities
Design, build, and deploy autonomous AI agents using Amazon Bedrock, AgentCore, and related frameworks.
Apply machine‑vision and feature‑extraction techniques to home attributes (photos, plans, finishes) for premium pricing and personalization.
Engineer and maintain scalable data pipelines and systems that support all models and agents.
Integrate agents with enterprise systems and protocols (MCP servers, A2A, internal APIs).
Design and run experiments (A/B tests, multi‑armed bandits, uplift models) to optimize performance.
Ensure observability and reliability of deployed agents (logging, evaluation, monitoring, drift detection).
Gather stakeholder feedback and adapt solutions for adoption and measurable impact.
Translate complex data‑science concepts into clear recommendations, stories, and visualizations for executives and non‑technical audiences.
Favor incremental, explainable solutions that deliver quick wins and scale over time.
Drive experimentation with new tools and approaches, ensuring robustness, governance, and scalability in production deployments.
Share learnings with the broader team to raise the bar on data‑science and agent‑centric development.
Manage timelines and expectations transparently with the data‑science team and business stakeholders.
Requirements
Bachelor’s or Master’s degree in Statistics, Economics, Math, Computer Science, Data Science, Machine Learning, or related field (or equivalent experience).
5+ years of relevant experience (1+ with PhD, 3+ with MS) in data science, ML engineering, or applied AI development delivering production‑ready models and systems.
Strong proficiency in Python and SQL, owning the full data‑science stack (data pipelines + models + deployment).
Hands‑on experience with AI development frameworks (LangChain, Strands, Amazon Bedrock, AgentCore, or equivalent).
Experience with experimentation frameworks (A/B testing, uplift modeling, multi‑armed bandits, causal ML).
Exposure to machine‑vision techniques (CNNs, transfer learning, embeddings) and NLP techniques (embeddings, transformers, prompt engineering).
Understanding of AI agent observability (evaluation frameworks like LangFuse, RAGAS, Weights & Biases, custom monitoring).
Experience with system integrations: APIs, A2A protocol, MCP servers, orchestration pipelines.
Comfort working with large‑scale, imperfect real‑world datasets and making progress despite complexity.
Strong engineering skills: design and maintain production pipelines, microservices, and scalable systems.
Proven ability to navigate ambiguity, rapidly prototype, and move solutions into production.
Collaborative communicator who can align technical solutions with business priorities across diverse stakeholders.
Bonus: experience with RAG pipelines, LLM fine‑tuning, RLHF, multi‑agent orchestration, feature stores, survival analysis/churn modeling, and attribution modeling.
Physical & Office Requirements Primarily a sedentary office position. Requires ability to operate computer equipment, speak, hear, bend, stoop, reach, lift, move, and carry up to 25 lbs. Finger dexterity necessary.
EEO Statement Lennar is an equal‑opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.
#J-18808-Ljbffr