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# Data Scientist

- **Company:** Intersources Inc.
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data as a Services, Python (Programming Language), Machine Learning, Natural Language Processing, OpenAI, Tensorflow, Azure Machine Learning, SQL Databases, Feature Engineering, Graph Neural Networks, Pytorch, LangChain, Prophet, Retrieval-Augmented Generation, Large Language Models, Snowflake, Model Validation, Agentic-AI, AI Platforms, Pyspark, LangSmith, Scikit Learn, Kubernetes, Information Technology, Optimization Algorithms, HuggingFace, Xgboost, AutoGen, Machine Learning Operations, Google Gemini, KServe, Unsupervised Learning
- **Published:** October 1, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/33175299#/jobs/33175299

## About the Role

* Experience with LangChain, LangGraph, AutoGen, Hugging Face, OpenAI, Gemini, or comparable AI frameworks.
 * Experience with ML observability tools such as Weights & Biases, LangSmith, TensorBoard, or similar platforms.
 * Knowledge of computer vision, graph neural networks, adversarial machine learning, and optimization techniques.
 * Experience with Snowflake, PySpark, OneLake, SageMaker, Azure AI Services, and data visualization platforms.
 * Professional experience in data science, machine learning, or AI engineering.
 * Advanced proficiency in Python and SQL.
 * Strong experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, or comparable frameworks.
 * Hands-on experience with statistical modeling, supervised and unsupervised learning, feature engineering, and model evaluation.
 * Experience building production solutions using LLMs, NLP, RAG, embeddings, fine-tuning, and agentic AI frameworks.
 * Experience with time-series forecasting methods such as Prophet, ARIMA, SARIMA, and gradient-boosting models.
 * Experience deploying scalable ML pipelines using Kubernetes, Kubeflow, KServe, or equivalent technologies.
 * Working knowledge of cloud AI and data services across Azure, AWS, or GCP.
 * Experience with relational, analytical, graph, and vector databases.
 * Strong problem-solving, stakeholder engagement, communication, and cross-functional collaboration skills.
 * Master's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, or a related quantitative discipline.