The Value Maximizer
Data Scientist
Build and optimize classification, regression, and forecasting models using classical ML and deep learning techniques
Develop and deploy deep learning architectures including LSTMs, transformers, and other sequence-based models for time-series, NLP, and anomaly detection
Design and implement NLP pipelines for text classification, semantic search, summarization, and question answering using transformer-based models (e.g., BERT, T5, GPT)
Create RAG (retrieval-augmented generation) pipelines integrating LLMs with vector databases (e.g., FAISS, Pinecone, Weaviate) and document indexing frameworks
Apply and fine-tune LLMs (e.g., OpenAI, Mistral, LLaMA, Cohere) for domain-specific tasks using supervised fine-tuning or LoRA/QLoRA methods
Build and orchestrate multi-agent AI systems using frameworks like LangGraph, CrewAI, or OpenAgents to support tool-using, autonomous agents for decision-making workflows
Collaborate with data engineers, product managers, and stakeholders to translate business needs into production-ready solutions
Mentor and support junior data scientists through code reviews, model design feedback, and collaborative experimentation
Promote best practices in reproducible modeling, responsible AI, and scalable deployment
Required Skills & Experience
5+ years of experience in data science or applied machine learning, with a strong background in both classical and deep learning methods
Hands-on experience with Python, and libraries/frameworks such as scikit-learn, pandas, PyTorch, TensorFlow, Hugging Face Transformers, and LangChain
Strong understanding of classification metrics, feature engineering, model validation, and hyperparameter tuning
Demonstrated experience with LLMs, including fine-tuning, prompt engineering, and retrieval-augmented generation techniques
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Other
Industries
IT Services and IT Consulting
Jersey City, NJ
Salary: $116,000 - $145,000
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Build and optimize classification, regression, and forecasting models using classical ML and deep learning techniques
Develop and deploy deep learning architectures including LSTMs, transformers, and other sequence-based models for time-series, NLP, and anomaly detection
Design and implement NLP pipelines for text classification, semantic search, summarization, and question answering using transformer-based models (e.g., BERT, T5, GPT)
Create RAG (retrieval-augmented generation) pipelines integrating LLMs with vector databases (e.g., FAISS, Pinecone, Weaviate) and document indexing frameworks
Apply and fine-tune LLMs (e.g., OpenAI, Mistral, LLaMA, Cohere) for domain-specific tasks using supervised fine-tuning or LoRA/QLoRA methods
Build and orchestrate multi-agent AI systems using frameworks like LangGraph, CrewAI, or OpenAgents to support tool-using, autonomous agents for decision-making workflows
Collaborate with data engineers, product managers, and stakeholders to translate business needs into production-ready solutions
Mentor and support junior data scientists through code reviews, model design feedback, and collaborative experimentation
Promote best practices in reproducible modeling, responsible AI, and scalable deployment
Required Skills & Experience
5+ years of experience in data science or applied machine learning, with a strong background in both classical and deep learning methods
Hands-on experience with Python, and libraries/frameworks such as scikit-learn, pandas, PyTorch, TensorFlow, Hugging Face Transformers, and LangChain
Strong understanding of classification metrics, feature engineering, model validation, and hyperparameter tuning
Demonstrated experience with LLMs, including fine-tuning, prompt engineering, and retrieval-augmented generation techniques
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Other
Industries
IT Services and IT Consulting
Jersey City, NJ
Salary: $116,000 - $145,000
#J-18808-Ljbffr