Data Scientist at Later

Candidates must possess a Bachelor's degree in computer science or a related field. Experience in the full machine learning lifecycle, including development, deployment, and maintenance of data science solutions, is required. Proficiency with Microsoft Azure technologies such as Azure Machine Learning and Azure Databricks, along with strong programming skills in Python or PySpark, is essential. A solid understanding of supervised and unsupervised learning algorithms and concepts, alongside experience in data preparation, feature engineering, and data engineering practices, is necessary. Experience in optimizing and tuning machine learning solutions for large datasets, outstanding verbal and written communication skills, and excellent presentation and whiteboarding abilities are also required. Experience communicating technical concepts to non-technical audiences and collaborating with business stakeholders to design AI solutions is crucial. Experience building solutions with Azure AI Services, Microsoft Fabric, or Azure Data Factory is preferred. Certifications like AI-102, DP-100, or Databricks ML Data Scientist certifications are a plus, as is experience with GitHub or Azure DevOps. Prior consulting and business development experience is also a plus.