Gen AI + Data Science Specialist

Job Overview

We are looking for a Gen AI + Data Science Specialist who combines deep data science expertise with hands-on Generative AI skills. The ideal candidate will leverage statistical modeling, data analytics, and Gen AI technologies to derive actionable insights and build intelligent, data-driven AI solutions.

Note

Applicants should have hands-on experience in Gen AI + Python and knowledge of Large Language Models (LLMs), RAG pipelines, embeddings, and prompt engineering. Practical experience with AI-driven and GenAI applications is preferred.

Key Responsibilities

Apply advanced statistical methods, machine learning, and Gen AI techniques to solve complex business problems. Build and deploy Gen AI solutions such as intelligent document processing, automated report generation, and AI-powered analytics. Develop and optimize RAG pipelines, embeddings, and LLM-based workflows for data-centric applications. Perform exploratory data analysis (EDA), feature engineering, and predictive modeling on large-scale datasets. Design prompt engineering strategies and fine-tune LLMs for domain-specific data science tasks. Create interactive dashboards, visualizations, and data stories for stakeholders and leadership. Collaborate with engineering and product teams to operationalize data science models and Gen AI solutions. Stay current with emerging trends in Gen AI, NLP, and advanced analytics to drive innovation. Must-Have Skills

Strong expertise in Data Science statistical modeling, hypothesis testing, regression, clustering, and classification. Hands-on experience with Python and data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn). Working knowledge of Generative AI, Large Language Models (LLMs), and NLP techniques. Experience with RAG pipelines, embeddings, vector databases, and prompt engineering. Proficiency in SQL and experience working with structured and unstructured data. Experience with data visualization tools (Power BI, Tableau, or Plotly). Familiarity with cloud-based AI/ML services (Azure AI, AWS SageMaker, or GCP Vertex AI). Good-to-Have Skills

Experience with LangChain, LlamaIndex, or similar Gen AI orchestration frameworks. Knowledge of Deep Learning frameworks (TensorFlow, PyTorch) for advanced modeling. Exposure to big data technologies (Spark, Databricks, or Hadoop). Experience with A/B testing, experimentation design, and causal inference. Job Overview

We are looking for a Gen AI + Data Science Specialist who combines deep data science expertise with hands-on Generative AI skills. The ideal candidate will leverage statistical modeling, data analytics, and Gen AI technologies to derive actionable insights and build intelligent, data-driven AI solutions.

Note

Applicants should have hands-on experience in Gen AI + Python and knowledge of Large Language Models (LLMs), RAG pipelines, embeddings, and prompt engineering. Practical experience with AI-driven and GenAI applications is preferred.

Key Responsibilities

Apply advanced statistical methods, machine learning, and Gen AI techniques to solve complex business problems. Build and deploy Gen AI solutions such as intelligent document processing, automated report generation, and AI-powered analytics. Develop and optimize RAG pipelines, embeddings, and LLM-based workflows for data-centric applications. Perform exploratory data analysis (EDA), feature engineering, and predictive modeling on large-scale datasets. Design prompt engineering strategies and fine-tune LLMs for domain-specific data science tasks. Create interactive dashboards, visualizations, and data stories for stakeholders and leadership. Collaborate with engineering and product teams to operationalize data science models and Gen AI solutions. Stay current with emerging trends in Gen AI, NLP, and advanced analytics to drive innovation. Must-Have Skills

Strong expertise in Data Science statistical modeling, hypothesis testing, regression, clustering, and classification. Hands-on experience with Python and data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn). Working knowledge of Generative AI, Large Language Models (LLMs), and NLP techniques. Experience with RAG pipelines, embeddings, vector databases, and prompt engineering. Proficiency in SQL and experience working with structured and unstructured data. Experience with data visualization tools (Power BI, Tableau, or Plotly). Familiarity with cloud-based AI/ML services (Azure AI, AWS SageMaker, or GCP Vertex AI). Good-to-Have Skills

Experience with LangChain, LlamaIndex, or similar Gen AI orchestration frameworks. Knowledge of Deep Learning frameworks (TensorFlow, PyTorch) for advanced modeling. Exposure to big data technologies (Spark, Databricks, or Hadoop). Experience with A/B testing, experimentation design, and causal inference.