AIData Scientist – Python | PySpark | ETL | Machine Learning | Predictive Analytics | LLM | RAG | MCP | Cloud

Employment Type: Full-Time Experience: IT Exp 10+ Years Python Experience: Min10+ Years PySpark Experience: Min5+ Years

AI / Data ScienceExperience: Min 3+ Years

About the Role

Cloudoplus is seeking a highly skilled AI Data Scientist with strong expertise in Python, PySpark, ETL, Machine Learning, Predictive Analytics,

Generative AI, LLMs, RAG, MCP, and Cloud Technologies to support enterprise-scale U.S.-based client projects.

The ideal candidate will have extensive experience building data-driven solutions, developing advanced machine learning models, designing AI-powered applications, and delivering business insights throughpredictive analytics and intelligent automation.

If you are passionate about solving complex business problems using AI, Machine Learning, and Data Science technologies, we'd love to hear from you.

Key Responsibilities

- Design, develop, and maintainscalable ETL pipelines usingPython, PySpark, and up-to-date data engineering frameworks.
- Process and transform large-scale structured and unstructured datasets for enterprise analytics and AI applications.
- Build, train, validate, and deploy Machine Learning models for predictive analytics, forecasting, recommendation systems,classification, and clustering.
- Develop advanced PredictiveAnalytics solutions tosupport strategic business decision-making.
- Design and implement Generative AI applications using Large Language Models (LLMs).
- Build and optimizeRetrieval-Augmented Generation (RAG)





architectures for enterprise knowledge management and intelligent search solutions.
- Develop AI solutions using Model Context Protocol (MCP) to integrate AI models with enterprise systems,tools, APIs, and external data sources.
- Train, evaluate, and optimizevarious Machine Learning algorithms to improve accuracy, performance, and scalability.
- Work with foundation modelsincluding OpenAI, Claude, Gemini, Llama, and Hugging Face models.
- Perform feature engineering, model tuning, model evaluation, and production deployment.
- Develop end-to-end AI/ML pipelines from data ingestionthrough model deployment and monitoring.
- Collaborate with business stakeholders, architects, product teams,and client teams to deliver enterprise AI and analytics solutions.
- Present analytical findings, insights,and recommendations to technical and non-technical stakeholders.
- Ensure AI solutions meet performance, scalability, security, and governance requirements.
- Support enterprise data modernization, AI transformation, and cloud migration initiatives.

Technologies

Python • PySpark • ETL • Spark SQL • Databricks • Machine Learning • ML Algorithms • Predictive Analytics • Statistical

Modeling • Data Science• Generative AI • LLM • NLP • RAG • MCP

- OpenAI • Claude • Gemini • Llama • Hugging Face • LangChain • LlamaIndex • TensorFlow • PyTorch • Scikit-Learn • XGBoost • SQL
- PostgreSQL • MongoDB • Hadoop • Spark • AWS • Azure • Google Cloud Platform (GCP) • Docker • Kubernetes • Git • CI/CD

📌 Data Scientist (Ontario)
🏢 Cloudoplus
📍 Ontario