Data Science Intern

Data Science – EU Region

Location: European UnionWork Arrangement: RemoteWe are hiring on behalf of one of our clients for a Data Science role focused on applying statistical analysis, machine learning, and data-driven approaches to solve complex business and technical problems.Key ResponsibilitiesAnalyse large and complex datasets to identify patterns, trends, relationships, and actionable insights.Develop, test, and implement statistical and machine learning models to address business and operational requirements.Collect, clean, transform, and prepare data from multiple structured and unstructured sources.Perform exploratory data analysis to understand datasets and identify relevant variables and relationships.Develop predictive models for forecasting, classification, regression, segmentation, and other analytical use cases.Evaluate model performance using appropriate statistical and machine learning metrics.Perform feature engineering and feature selection to improve model performance and reliability.Conduct statistical analysis and hypothesis testing to support data-driven decision-making.Build data visualisations and analytical reports to communicate findings effectively.Translate complex analytical results into clear recommendations for technical and non-technical stakeholders.Collaborate with Data Engineers, Data Analysts, Software Engineers, Product Teams, and business stakeholders.Work with large-scale datasets and contribute to scalable data science solutions.Develop reproducible and well-documented analytical workflows.Monitor model performance and identify opportunities for model improvement.Support the deployment and integration of machine learning models into business applications and production environments.Maintain documentation covering analytical methodologies, models, assumptions, and results.Ensure data quality, accuracy, privacy, and appropriate handling of sensitive information.Stay informed about emerging developments in machine learning, artificial intelligence, statistics, and data science.Required Qualifications and SkillsDegree or equivalent qualification in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, or a related field.Strong programming skills in Python or R.Strong knowledge of statistics, probability, and mathematical concepts used in data science.Experience working with libraries and frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.Strong SQL skills and understanding of relational databases.Experience with data cleaning, preprocessing, exploratory data analysis, and feature engineering.Understanding of supervised and unsupervised machine learning techniques.Knowledge of model evaluation, validation, and performance optimisation.Strong analytical and problem-solving abilities.Ability to communicate technical findings clearly to both technical and non-technical audiences.Strong attention to detail and ability to work with complex datasets.Preferred SkillsExperience developing and deploying machine learning models in production environments.Knowledge of deep learning techniques and neural network architectures.Experience with natural language processing, computer vision, recommendation systems, or time-series modelling.Familiarity with Generative AI, Large Language Models, and modern AI technologies.Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.Knowledge of platforms and tools such as Databricks, MLflow, Spark, or similar technologies.Experience with MLOps practices, model monitoring, versioning, and automated deployment.Familiarity with Docker, Kubernetes, and containerised machine learning environments.Experience working with APIs and integrating machine learning solutions into applications.Knowledge of data visualisation tools such as Power BI, Tableau, or similar platforms.Experience working with distributed computing and large-scale data processing.Understanding of data governance, privacy, security, and responsible AI principles.Familiarity with Git, CI/CD pipelines, and Agile development practices.Experience working with cloud-based data platforms and data warehouses.Knowledge of experimental design, A/B testing, and advanced statistical modelling.Ability to evaluate emerging AI and machine learning technologies and identify practical business applications.What We OfferRemote working opportunity within the EU region.Opportunity to work on real-world data science, machine learning, and AI projects.Exposure to modern data science tools, frameworks, cloud platforms, and AI technologies.Opportunity to work with diverse datasets and solve practical business and technical challenges.Collaborative working environment with professionals across data, technology, and business functions.Opportunity to contribute to data-driven decision-making and innovative technology solutions.Exposure to end-to-end data science workflows, from data preparation and modelling to deployment and optimisation.Opportunities to strengthen practical experience in machine learning, predictive analytics, and artificial intelligence.Opportunity to work with cross-functional teams and gain broader exposure to technology and business processes.Professional environment that encourages learning, knowledge sharing, and continuous development.Opportunity to enhance technical, analytical, and problem-solving skills through practical projects.Exposure to emerging technologies and evolving practices within the data science and AI ecosystem.