Data Scientist ~ NLP & Generative AI Focus

Title: Data Scientist ~ NLP & Generative AI Focus

Location: Remote

Duration: Temporary

Compensation: will vary based on experience and project scope

Summary:

Fausto Commercial is seeking a Data Scientist to lead the development of a cutting-edge, voice-activated real estate assistant. This intelligent system will use natural language processing (NLP) to interpret spoken property inquiries, match them to listings in real time, and capture caller details into a CRM for seamless lead management. Future phases will introduce predictive features that identify potential buyers or tenants for new listings based on historical inquiry patterns—streamlining prospecting and boosting conversion rates.

About the Role:

We are seeking an exceptional Data Scientist with a strong background in Natural Language Processing (NLP), Machine Learning (ML), and Big Data technologies to join our fast-growing, innovation-driven team. This role involves building scalable data pipelines, developing state-of-the-art NLP models, and applying generative AI techniques to solve complex business challenges. The ideal candidate is equally passionate about deep technical work and practical applications of AI to drive real-world impact.

Must-Have Skills:

• Bachelor's degree in Computer Science, Data Science, or in a quantitatively or intellectually rigorous discipline
• 5+ years in a similar role
• Software Engineering & Programming: Strong command of Python and SQL. Strong grasp of OOP principles (encapsulation, inheritance, abstraction, polymorphism) to build maintainable, modular codebases.
• Big Data & Data Engineering Pipelines: Experience with building scalable ETL/ELT pipelines that extract, clean, and load large datasets into data lakes/warehouses.
• Software Engineering & Programming: Strong command of Python and SQL. Strong grasp of OOP principles (encapsulation, inheritance, abstraction, polymorphism) to build maintainable, modular codebases.
• Natural Language Processing (NLP): Proficiency in both traditional and neural NLP techniques. Strong background in feature engineering for text data (TF-IDF, word2vec, FastText) and a solid grasp of transformer architectures. Experience with NLP libraries like spaCy and NLTK for text preprocessing and analysis.
• Vector Databases & Semantic Search: Deep understanding of vector embeddings and their application. Experience with modern vector stores (e.g., Pinecone, Weaviate, Milvus) for building Retrieval-Augmented Generation (RAG) systems. Skilled in using these tools for semantic search, similarity-based retrieval, and building conversational AI agents.
• Generative AI & Large Language Models (LLMs): Hands-on experience with state-of-the-art LLMs (e.g., Llama, Mistral, GPT-4) and generative AI models. Expertise in fine-tuning foundational models for specific business tasks (e.g., classification, summarization, speech intent mapping). Proficient with frameworks like Hugging Face Transformers and LangChain for building production-ready applications.
• Machine Learning & Model Ops: Skilled in training and deploying deep learning models using frameworks such as PyTorch, TensorFlow, and Keras. Expertise in the MLOps lifecycle, including model versioning, pipeline orchestration with tools like MLflow or Kubeflow, and continuous monitoring/retraining of models in production environments.
• Data Access Tools: Proficient in Python and SQL for data manipulation and modeling.

Nice to Have:

• Experience with GitHub and REST APIs

Visualization tools like Power BI, Django, or Flask

• Experimentation with CLOSED - source models