Jobs via Dice
Job Title:
Senior Data Scientist
Location:
Hartford, CT (Hybrid)
Employment Type:
Contract
Experience required:
10+ years in Data Science / Machine Learning (with strong GenAI focus)
Role Overview:
We are seeking a
Senior/Lead Data Scientist
with
10+ years of experience
and deep expertise in
Generative AI, Large Language Models (LLMs),
and
Python
to lead the design, development, and deployment of advanced AI solutions. This role will play a critical part in driving enterprise-scale GenAI initiatives, defining best practices, and mentoring teams while delivering high-impact, production-ready AI systems. The ideal candidate has hands‑on experience building and scaling
LLM‑powered applications , architecting
RAG systems , and translating complex business problems into robust AI‑driven solutions.
Key Responsibilities
Lead the end-to-end design, development, and deployment of Generative AI and LLM-based solutions at enterprise scale.
Architect and implement LLM-powered use cases including summarization, classification, extraction, semantic search, and conversational AI assistants.
Design and optimize prompt engineering strategies, RAG architectures, and fine‑tuning / adapter‑based approaches (LoRA, PEFT, etc.).
Apply advanced NLP and ML techniques including text classification, topic modeling, embeddings, clustering, regression, and causal inference.
Build scalable Python-based ML/GenAI pipelines, evaluation frameworks, and reusable components.
Drive model evaluation, experimentation, and performance benchmarking for GenAI systems.
Collaborate with product, engineering, and business stakeholders to translate requirements into AI solutions.
Mentor junior and mid-level data scientists; provide technical leadership and code reviews.
Contribute to AI governance, responsible AI practices, and model risk management where applicable.
Key Qualifications
10+ years of experience in Data Science, Machine Learning, or Applied AI.
Proven hands‑on experience with Generative AI and LLMs in production environments.
Expert-level Python programming skills, including:
pandas, NumPy, scikit‑learn
GenAI frameworks such as LangChain, LlamaIndex, or direct SDK usage (OpenAI, Azure OpenAI, Vertex AI, Hugging Face)
Strong experience with:
Embeddings, vector databases, and semantic search
Retrieval‑Augmented Generation (RAG) patterns
Prompt engineering and LLM evaluation techniques
Solid foundation in statistics and experimentation:
Hypothesis testing, confidence intervals, power analysis
Experimental design and A/B testing
Advanced understanding of object‑oriented and functional programming patterns for ML workflows.
Experience deploying models in cloud environments (AWS, Azure, or Google Cloud Platform) is highly desirable.
Experience leading or architecting enterprise GenAI platforms.
Familiarity with MLOps/LLMOps tools and CI/CD pipelines.
Experience with multimodal AI (text, image, audio).
Background in regulated industries (finance, healthcare, telecom).
#J-18808-Ljbffr
Senior Data Scientist
Location:
Hartford, CT (Hybrid)
Employment Type:
Contract
Experience required:
10+ years in Data Science / Machine Learning (with strong GenAI focus)
Role Overview:
We are seeking a
Senior/Lead Data Scientist
with
10+ years of experience
and deep expertise in
Generative AI, Large Language Models (LLMs),
and
Python
to lead the design, development, and deployment of advanced AI solutions. This role will play a critical part in driving enterprise-scale GenAI initiatives, defining best practices, and mentoring teams while delivering high-impact, production-ready AI systems. The ideal candidate has hands‑on experience building and scaling
LLM‑powered applications , architecting
RAG systems , and translating complex business problems into robust AI‑driven solutions.
Key Responsibilities
Lead the end-to-end design, development, and deployment of Generative AI and LLM-based solutions at enterprise scale.
Architect and implement LLM-powered use cases including summarization, classification, extraction, semantic search, and conversational AI assistants.
Design and optimize prompt engineering strategies, RAG architectures, and fine‑tuning / adapter‑based approaches (LoRA, PEFT, etc.).
Apply advanced NLP and ML techniques including text classification, topic modeling, embeddings, clustering, regression, and causal inference.
Build scalable Python-based ML/GenAI pipelines, evaluation frameworks, and reusable components.
Drive model evaluation, experimentation, and performance benchmarking for GenAI systems.
Collaborate with product, engineering, and business stakeholders to translate requirements into AI solutions.
Mentor junior and mid-level data scientists; provide technical leadership and code reviews.
Contribute to AI governance, responsible AI practices, and model risk management where applicable.
Key Qualifications
10+ years of experience in Data Science, Machine Learning, or Applied AI.
Proven hands‑on experience with Generative AI and LLMs in production environments.
Expert-level Python programming skills, including:
pandas, NumPy, scikit‑learn
GenAI frameworks such as LangChain, LlamaIndex, or direct SDK usage (OpenAI, Azure OpenAI, Vertex AI, Hugging Face)
Strong experience with:
Embeddings, vector databases, and semantic search
Retrieval‑Augmented Generation (RAG) patterns
Prompt engineering and LLM evaluation techniques
Solid foundation in statistics and experimentation:
Hypothesis testing, confidence intervals, power analysis
Experimental design and A/B testing
Advanced understanding of object‑oriented and functional programming patterns for ML workflows.
Experience deploying models in cloud environments (AWS, Azure, or Google Cloud Platform) is highly desirable.
Experience leading or architecting enterprise GenAI platforms.
Familiarity with MLOps/LLMOps tools and CI/CD pipelines.
Experience with multimodal AI (text, image, audio).
Background in regulated industries (finance, healthcare, telecom).
#J-18808-Ljbffr