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Data Scientist
Negotiable Salary
Indeed
Full-time
Onsite
No experience limit
No degree limit
111411, Los Mártires, Bogotá, Colombia
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Description

**Job Description** Develop medium-to-advanced complexity products, with quality and according to the assigned date and time. **EDUCATION** * Professional in Engineering, Statistics and/or Mathematics with knowledge in Machine Learning. Proficiency in R, Python, Scala software. * Recent training related to AI/Generative AI (LLM) implementation: courses in Azure AI/Azure OpenAI (e.g., AI-102\), Google Cloud Generative AI/Vertex AI, AWS Bedrock, Databricks Generative AI, Prompt Engineering, RAG, and Responsible AI. Verifiable credentials (badges) and portfolio (GitHub/notebooks) are valued. * Complementary: data security and governance (PII/PHI, compliance), agile methodologies (Scrum/Kanban), and best practices in MLOps/LLMOps. **EXPERIENCE** * Minimum of 1\-2 years implementing analytical models. * Demonstrable experience in the end-to-end cycle from exploration to model production. * Analyze and interpret qualitative and quantitative data using existing statistical methods. * Extensive experience and high level of knowledge in ML (logistic regression, decision trees, time series, clustering, among others). * Knowledge in AI such as: o NLP o Computer Vision o Others * Additional (GenAI/LLM): + Participation in projects with Generative AI/LLM or, otherwise, proven knowledge (use cases, PoC/prototypes or verifiable deliverables). + Design and evaluation of prompts; fine-tuning when applicable; quality evaluation (factual accuracy, safety, usefulness, toxicity). + Knowledge of patterns such as RAG, assistants, and augmented search; integration with APIs and cloud services (Azure OpenAI/OpenAI API, Google Vertex AI, AWS Bedrock). + Development in Python/SQL; building services (e.g., FastAPI), containers (Docker), version control (Git), and MLOps/LLMOps practices (MLflow, Weights \& Biases, continuous evaluation, quality monitoring, costs and latency). **DESIRABLE** * ML and AI services on any cloud (Azure, AWS, GCP). * Production implementation of LLM-based solutions (RAG, assistants, knowledge generation/synthesis) with guardrails, hallucination mitigation, and privacy/security controls. * LLMOps practices: evaluation datasets, prompt traceability, quality/cost/drift monitoring, and A/B testing. * Recent studies and/or certifications related to AI/Generative AI implementation. * Public contributions: case studies, technical publications, talks, or open-source projects. * Intermediate/advanced English for technical documentation and coordination with vendors. **Functional Responsibilities:** + End\-to\-end execution of data/ML/GenAI solutions: discovery, set\-up, planning, execution, validation, final preparation, and release to production. + Design and develop analytical models (regression, trees, time series, clustering, NLP, vision) and LLM-based solutions (RAG, assistants, semantic search, internal chat), including prompt design/evaluation and, when applicable, fine-tuning. + Ensure data governance, security, and privacy; implement guardrails and principles of Responsible AI. + Solve complex problems and propose innovative solutions; work autonomously. **Skills** Positive Attitude III Effective Communication III Customer Focus III Innovative Thinking III Teamwork III Change Management III Knowledge Management IV Commitment III Negotiation II Results Orientation III Analytical Thinking III Problem Solving II Empowerment I Performance Management I Leadership I expert novice expert expert expert expert expert master expert intermediate expert expert intermediate novice novice novice**Qualifications****KEYWORDS** * Bert Model, Spark, Torch, Tensorflow * Gen AI, LLM, RAG, Prompt Engineering * LLM Evaluation, Guardrails, Responsible AI * LLMOps, MLOps, MLflow, Weights \& Biases * LangChain, LlamaIndex **About Us** We believe in Latin America's innovative potential and passionately live digital transformation and convergence, which is why we want to help you maximize your business capabilities. Now is the time to unify silos, converge around a common purpose, and connect technologies to transform them into value. Axity, connections that transform

Source:  indeed View original post
Valentina Rodríguez
Indeed · HR

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