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# Senior Data Scientist

- **Company:** Greece, L.L.C.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Database, Data Cleansing, Data Governance, Data Visualization, Information Extraction, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Power BI, Azure Machine Learning, Search Technologies, Unstructured Data, Management of Software Versions, Explainable AI (XAI), Feature Engineering, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Pandas, Matplotlib, AI Platforms, Scikit Learn, Information Technology, Performance Monitor, Plotly, Machine Learning Operations, Azure Synapse Analytics, Databricks
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8gzcakvi

## About the Role

* 5-7 years of professional experience in Data Science, Machine Learning, Advanced Analytics, or a closely related discipline.
 * A university degree in Computer Science, Mathematics, Statistics, Engineering, Economics, Data Science, or another quantitative discipline.

Core Competencies & Knowledge

 * Advanced proficiency in Python and commonly used data science libraries such as pandas, NumPy, scikit-learn, matplotlib, and seaborn.
 * Strong understanding of statistics, machine learning, data modelling, feature engineering, model evaluation, and experimental design.
 * Experience working with cloud-based data and AI platforms, preferably Microsoft Azure, Azure Machine Learning, Azure Databricks, or Azure Synapse Analytics.
 * Practical knowledge of Generative AI, Large Language Models, prompt engineering, embeddings, vector search, and Retrieval-Augmented Generation.
 * Familiarity with MLOps and the deployment, versioning, monitoring, and governance of machine-learning models.
 * Experience with data visualisation and business intelligence tools such as Power BI or Plotly.
 * Understanding of data governance, model risk, explainable AI, responsible AI, and ethical use of data.
 * Strong problem-solving skills and the ability to connect technical solutions with business objectives.
 * Excellent written and verbal communication skills in Greek and English.

## Description

This role is ideal for an experienced professional who combines strong foundations in data science and machine learning with practical knowledge of Artificial Intelligence, including Generative AI and Large Language Models.

You will work on real business challenges, transforming structured and unstructured data into intelligent models, actionable insights, and scalable AI-powered solutions. Working closely with business stakeholders, Data Engineers, technology teams, and governance functions, you will help shape how data and AI are applied across the organization., * Design, develop, evaluate, and improve predictive, descriptive, and prescriptive models using statistical and machine-learning techniques.

 * Analyse structured and unstructured datasets to identify patterns, trends, risks, and opportunities that support strategic decision-making.
 * Develop AI and Generative AI solutions, including use cases based on Large Language Models, Natural Language Processing, document intelligence, and intelligent automation.
 * Build robust data science pipelines covering data preparation, feature engineering, model training, validation, explainability, and performance monitoring.
 * Work with Data Engineers to ensure the quality, accessibility, relevance, and appropriate use of data throughout the analytical lifecycle.
 * Collaborate with business stakeholders to translate business requirements into clearly defined analytical and AI use cases.
 * Design experiments and analytical frameworks to validate hypotheses and assess business impact.
 * Communicate complex findings through compelling visualisations, presentations, and clear recommendations for technical and non-technical audiences.
 * Support the development of reusable methodologies, components, and best practices across the Data and AI ecosystem.
 * Provide technical guidance and knowledge sharing to colleagues involved in data science and AI initiatives.