Data Scientist

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Develop, assess, and enhance machine learning and generative AI solutions for Intermedia's Digital Agent Platform.

• Utilize LLMs, NLP, retrieval techniques, and advanced AI methodologies to enhance agent comprehension and performance.

• Advance agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion.

• Conduct experiments with models, prompts, retrieval strategies, and agent configurations.

• Assess both commercial and open-source models based on quality, latency, scalability, and cost considerations.

• Design and refine Retrieval-Augmented Generation (RAG) solutions.

• Create embeddings, retrieval strategies, ranking methods, semantic search, and knowledge-retrieval techniques.

• Construct end-to-end pipelines that integrate LLMs, retrieval systems, enterprise knowledge, and agent workflows.

• Identify and address hallucinations, inadequate retrieval, unsuitable responses, and other generative AI failure modes.

• Develop evaluation frameworks and conduct offline/online experiments to ensure digital agent quality.

• Implement statistical analysis, hypothesis testing, segmentation, and quantitative methods to assess AI performance.

• Establish metrics and benchmarks that connect model performance to customer and business outcomes.

• Analyze production behavior and feedback to pinpoint failure modes and identify opportunities for improvement.

• Collect, preprocess, analyze, and model both structured and unstructured data.

• Utilize Python, SQL, Spark, and related technologies to create scalable analytical and machine learning solutions.

• Develop features, datasets, pipelines, and analytical methodologies for model development and assessment.

• Collaborate with data and engineering teams to ensure reliable production ML/AI pipelines.

• Guarantee that solutions are reproducible, maintainable, and scalable for production.

• Work alongside Product, AI/ML Engineering, Software Engineering, and Data Science teams.

• Present findings, model performance, trade-offs, and recommendations to both technical and non-technical stakeholders.

• Engage in technical and design reviews.

• Mentor junior data scientists and contribute to knowledge-sharing initiatives.

⛳️ Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative discipline.

• Preferred: Master's degree.

• 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical domain.

• Extensive experience in developing and applying supervised and unsupervised machine learning models.

• Practical experience with generative AI, large language models, NLP, or other contemporary AI technologies.

• Proficient programming skills in Python.

• Familiarity with SQL and large-scale data processing technologies.

• Experience with PyTorch, TensorFlow, scikit-learn, or similar technologies.

• Strong knowledge of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance metrics.

• Experience handling large volumes of structured and unstructured data.

• Background in deploying and managing machine learning or AI solutions in production settings.

• Understanding of model quality, data integrity, bias, reliability, and considerations for production AI.

• Excellent problem-solving and analytical capabilities.

• Strong written and verbal communication skills.

• Ability to collaborate effectively across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams.

🏝️ Benefits

• Equal opportunity employer.

• Commitment to diversity and inclusion.

• Reasonable accommodations for documented disabilities or limitations as required by applicable laws.

• Non-discrimination based on protected characteristics.