Data Scientist

🕒 September 10

🇵🇹 Portugal – Remote

💵 €50k - €60k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Intermedia Cloud Communications

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

🏥 Healthcare

⚖️ Legal

💰 Venture Round on 2017-02

Consulting • Healthcare • Legal

Intermedia Cloud Communications is a leading provider of cloud-based communication solutions, specializing in unified communications, video conferencing, and various productivity tools. Their platform, Intermedia Unite, integrates voice, video, chat, and file management into a seamless user experience, enabling businesses to communicate and collaborate effectively from anywhere. With a focus on security and compliance, Intermedia serves a range of industries including healthcare, legal services, and financial services, helping organizations enhance productivity and customer care with advanced technology and support.

📋 Description

• Develop, evaluate, and improve machine learning and generative AI solutions for Intermedia's Digital Agent Platform • Apply LLMs, NLP, retrieval, and advanced AI techniques to improve agent understanding and performance • Improve agent reasoning, tool selection, knowledge retrieval, context management, personalization, and task completion • Experiment with models, prompts, retrieval strategies, and agent configurations • Evaluate commercial and open-source models based on quality, latency, scalability, and cost • Design and optimize Retrieval-Augmented Generation (RAG) solutions • Develop embeddings, retrieval strategies, ranking approaches, semantic search, and knowledge-retrieval techniques • Build end-to-end pipelines combining LLMs, retrieval systems, enterprise knowledge, and agent workflows • Identify and mitigate hallucinations, poor retrieval, inappropriate responses, and other generative AI failure modes • Develop evaluation frameworks and offline/online experiments for digital agent quality • Apply statistical analysis, hypothesis testing, segmentation, and quantitative methods to evaluate AI performance • Define metrics and benchmarks connecting model performance to customer and business outcomes • Analyze production behavior and feedback to identify failure modes and improvement opportunities • Gather, preprocess, analyze, and model structured and unstructured data • Use Python, SQL, Spark, and related technologies to build scalable analytical and machine learning solutions • Develop features, datasets, pipelines, and analytical approaches for model development and evaluation • Partner with data and engineering teams on reliable production ML/AI pipelines • Ensure solutions are reproducible, maintainable, and production-scale • Collaborate with Product, AI/ML Engineering, Software Engineering, and Data Science teams • Communicate findings, model performance, tradeoffs, and recommendations to technical and non-technical stakeholders • Participate in technical and design reviews • Mentor less experienced data scientists and contribute to knowledge sharing

🎯 Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Machine Learning, Analytics, or a related quantitative field • Master's degree preferred • 4+ years of professional experience in data science, machine learning, applied AI, or a related analytical field • Strong experience developing and applying supervised and unsupervised machine learning models • Hands-on experience with generative AI, large language models, NLP, or other modern AI technologies • Strong programming skills in Python • Experience with SQL and large-scale data processing technologies • Experience with PyTorch, TensorFlow, scikit-learn, or equivalent technologies • Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement • Experience working with large volumes of structured and unstructured data • Experience deploying and operating machine learning or AI solutions in production environments • Understanding of model quality, data quality, bias, reliability, and production AI considerations • Strong problem-solving and analytical skills • Strong written and verbal communication skills • Ability to collaborate across Data Science, AI/ML Engineering, Software Engineering, Product, and business teams

🏖️ Benefits

• Equal opportunity employer • Commitment to diversity and inclusion • Reasonable accommodations for identified disabilities or other limitations as required by applicable laws • Non-discrimination based on protected characteristics