Analyst - AI & Data Science
Role details
Job location
Tech stack
Job description
solutions such as LLM-based applications, NLP, computer vision, and predictive analytics, primarily on Microsoft Azure. Key Role Responsibilities Day-to-day you will: - Design and deliver end-to-end Data Science and AI solutions, from business understanding and data exploration to model deployment and monitoring. - Perform exploratory data analysis (EDA), feature engineering, and data preprocessing on structured and unstructured datasets. - Develop, train, evaluate, and optimize machine learning and deep learning models, selecting appropriate algorithms and validation strategies. - Contribute to Generative AI solutions, including LLM-based applications, prompt engineering, RAG architectures, and applied NLP use cases. - Translate business problems into analytical and ML formulations, clearly explaining trade-offs and results to both technical and non-technical stakeholders. - Support the preparation of client presentations, demos, and proposals, articulating analytical insights
Requirements
and AI-driven value. - Stay up to date with the latest advancements in Data Science, ML, DL, and GenAI, and actively share knowledge within the team. - Contribute to reusable assets such as code templates, analytical frameworks, and internal training materials. - Collaborate with senior team members and architects to identify opportunities where advanced analytics and AI can transform client operations. . Key Role Skill & Capability Requirements Core Skills - Strong foundation in Data Science and applied Machine Learning, including supervised and unsupervised learning. - Hands-on experience with ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow or equivalent). - Solid understanding of model evaluation, validation, and performance metrics. - Experience working with structured and unstructured data, including text data for NLP use cases. - Proficiency in Python for data analysis and ML development. AI & GenAI - Experience or strong interest in Generative AI, including LLMs, embeddings, prompt engineering, and retrieval-based approaches. - Familiarity with NLP, computer vision, forecasting, or optimization use cases is a strong plus. - Exposure to Azure AI / Azure Machine Learning / Azure OpenAI is highly valued. Professional Skills - Strong analytical and problem-solving mindset, with the ability to structure ambiguous problems. - Ability to communicate insights clearly in English and Spanish, both written and verbal. - Comfortable working in agile, client-facing environments. Preferred Education Background You likely hold a bachelor's and/or master's degree in computer science, Data Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. Equivalent practical experience is also valued. Preferred Years of Work Experience: - 3+ years of applied experience delivering Data Science, Machine Learning, or AI projects in real-world environments. - Experience over the last few years may be heavily focused on GenAI, but grounded in solid ML/DL and analytical fundamentals. What We offer - An accelerated and structured training program on Microsoft Azure and AI services. - Hands-on exposure to real client projects across computer vision, NLP, forecasting, and GenAI (Azure OpenAI, chatbots, RAG). - Continuous learning through certifications, mentoring, and internal communities of practice. .