Data Scientist

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    "datePosted": "2026-05-06T04:00:00.000Z",
    "description": "<h2>Overview</h2>\n<p><strong>About JAGGAER</strong></p>\n<p>JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes while enabling a highly resilient, responsible, and integrated supplier base. With 30 years of expertise, we specialize in solving complex procurement and supply chain challenges across various industries.</p>\n<p>Our 1,200+ global employees are obsessed with ensuring customers get full value from our products—ultimately enhancing and transforming their businesses.For more information, visit <strong>www.jaggaer.com</strong></p>\n<p><strong>Job Description</strong>We are seeking an innovative and highly skilled Data Scientist with expertise spanning conventional machine learning, Generative AI, Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG) solutions, and vector databases. This role involves leveraging advanced AI technologies, cloud platforms, and statistical modelling techniques to develop impactful solutions that drive measurable business value.</p>\n<p>As a Data Scientist, you will design, build, and optimize predictive and generative models, blending traditional ML approaches (supervised/unsupervised learning, time series forecasting, predictive analytics) with cutting-edge Generative AI and Agentic architectures. You will combine your strong foundation in data science, Python, SQL, cloud services, and vector databases to deliver scalable, production-ready solutions</p>\n<h2>Principal Responsibilities</h2>\n<ul>\n <li>Design, develop, and deploy machine learning models for prediction, classification, clustering, and time-series analysis.</li>\n <li>Develop Generative AI and LLM-powered solutions, including RAG pipelines for knowledge retrieval and contextual responses.</li>\n <li>Build and optimize Agentic AI systems capable of multi-step reasoning, tool orchestration, and autonomous workflows.</li>\n <li>Architect and manage vector database solutions (e.g., Pinecone, Weaviate, FAISS, Milvus) for embeddings, hybrid search, and RAG pipelines.</li>\n <li>Leverage advanced statistical and data science techniques to extract actionable insights from structured and unstructured datasets.</li>\n <li>Implement and scale AI/ML pipelines using AWS services (SageMaker, Lambda, API Gateway, Bedrock, S3, EKS).</li>\n <li>Collaborate with business stakeholders, engineers, and product teams to define use cases and deliver tailored AI/ML solutions.</li>\n <li>Write efficient, modular, and maintainable Python code for modeling, data processing, and deployment.</li>\n <li>Use advanced SQL for querying, transforming, and analyzing large relational datasets.</li>\n <li>Stay updated with emerging trends in LLMs, Agentic AI, RAG systems, and conventional ML to ensure continuous innovation.</li>\n <li>Maintain clear documentation for models, experiments, workflows, and processes.</li>\n</ul>\n<h2>Position Requirements</h2>\n<ul>\n <li>5+ years of experience as a Data Scientist or in a similar role.</li>\n <li>Proven expertise in conventional ML techniques: regression, classification, clustering, time-series forecasting, and predictive modelling.</li>\n <li>Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and Agentic AI solutions.</li>\n <li>Experience with LangChain, LangGraph, or similar agent frameworks.</li>\n <li>Strong proficiency in Python for machine learning, data manipulation, and deployment.</li>\n <li>Advanced SQL skills for working with large relational datasets.</li>\n <li>Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, EKS, API Gateway, S3).</li>\n <li>Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) as a core component of RAG pipelines.</li>\n <li>Familiarity with data engineering principles and cloud-based data pipelines.</li>\n <li>Strong problem-solving and analytical skills with the ability to translate business requirements into data-driven solutions.</li>\n <li>Passion for staying ahead of the curve in ML, AI, and multi-agent systems.</li>\n <li>Preferred Qualifications (Good-to-Have)</li>\n <li>Exposure to Model Context Protocol (MCP) for orchestrating AI applications.</li>\n <li>Background in MLOps/CI-CD pipelines for deploying and monitoring ML models at scale.</li>\n <li>Familiarity with deep learning frameworks (TensorFlow, PyTorch) for advanced modeling.<p><strong>What We Offer:</strong><strong> </strong></p><p>At JAGGAER, we are committed to supporting you and your family’s well-being. Your health is a priority, and we offer a range of programs to help you stay well and thrive. Our benefits include Health, Accidental Insurance, and Term Life. </p><p> </p><p><strong>Our Values - T.E.A.M :</strong></p><p>At JAGGAER, our business is about people. Our products are built on intellectual property, but the real differentiator is the teams behind them–the way we collaborate, innovate, solve problems and deliver for customers. TEAM gives us a common set of expectations for how we work together across products, cultures, and geographies. </p>\n  <ul>\n   <li>Transparency - Openness Builds Trust: Candor strengthens relationships, speeds decision-making, and ensures problems are solved together—with customers, teammates, and partners.</li>\n   <li>Entrepreneurial Spirit – Own It, Drive It, Make It: A scrappy, customer obsessed, problem-solving mindset is at the cornerstone of both organizational and personal growth </li>\n   <li>Accountability – Thumbs In, Not Fingers Out: We take responsibility ourselves before pointing elsewhere</li>\n   <li>Metrics-Driven Results – Outcomes Over Activities: Data and evidence guide our decisions, help us course-correct quickly, and ensure we’re delivering real impact. </li>\n  </ul><p><strong>EEO:</strong><strong> </strong></p><p>JAGGAER is a proud equal opportunity/affirmative action employer supporting workforce diversity. We do not discriminate based upon race, ethnicity, ancestry, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), marital status, caregiver status, sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, genetic information, military, or veteran status, mental or physical disability, or other applicable legally protected characteristics. </p>#LI-AR1</li>\n</ul>",
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