Data Scientist

As a Data Scientist you can expect to… Perform data discovery, profiling, cleaning, and exploratory analysis across structured and semi-structured enterprise datasetsDevelop predictive and statistical models that support forecasting, classification, segmentation, anomaly detection, and optimization use casesBuild and evaluate machine learning pipelines using Python-based frameworks within Azure analytics environmentsPrepare feature sets and training datasets aligned with business objectives and model performance requirementsPartner with Data Engineers and Integration Engineers to deploy models into production environments using Azure-based platformsSupport ingestion and preparation of data for analytics and intelligent applications across Microsoft Fabric, Synapse, and Azure DatabricksContribute to solutions supporting Copilot, Azure OpenAI, semantic search, and retrieval-based intelligent application scenariosDesign and execute experiments to validate model performance and improve prediction accuracyTranslate analytical outputs into clear business insights and recommendations for technical and functional stakeholdersDocument modeling assumptions, feature engineering approaches, evaluation results, and deployment workflowsSupport model monitoring activities including drift detection, retraining strategies, and performance trackingEnsure alignment with enterprise governance, data security, and responsible AI practices across engagementsStay current with emerging machine learning, analytics, and generative AI technologies within the Microsoft ecosystemYou’re great at… Handling multiple projects/tasks simultaneously  in a team environmentApplying statistical analysis and machine learning techniques to solve business problems using real-world enterprise datasetsBuilding predictive models using methods such as regression, classification, clustering, and time-series forecastingPreparing and transforming datasets for modeling through feature engineering and exploratory data analysisDeveloping machine learning workflows using Python and common ML libraries such as scikit-learn, TensorFlow, or PyTorchSupporting analytics environments such as Microsoft Fabric, Azure Databricks, Synapse, and Power BI data modelsCollaborating with Data Engineers and Integration Engineers to operationalize models within production data platformsDesigning experiments to evaluate model effectiveness and improve prediction accuracy over timeTranslating analytical findings into actionable insights for both technical and business stakeholdersWorking with cloud-based analytics and machine learning services, particularly within Microsoft Azure environmentsDocumenting modeling logic, assumptions, and outputs to support maintainability and governance requirementsSupporting feature engineering and model deployment within production data platformsPromoting the mission and Shared Values of our company  Sound interesting? If so, you’ll have… Bachelor’s degree in Computer Science, Information Technology, Statistics, Mathematics, or a related fieldStrong proficiency in Python and SQL for data preparation, modeling, and analysis workflowsDevelopment of predictive models using techniques such as regression, classification, clustering, or forecastingFamiliarity with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or similar frameworksSupport of analytics or modern data platforms such as Microsoft Fabric, Azure Databricks, Synapse, or Power BIWork within cloud-based analytics or machine learning environments, preferably Microsoft AzureExposure to model deployment workflows and collaboration with engineering teams supporting production implementationsClear communication of analytical insights to both technical and non-technical audiencesAbility to collaborate effectively across cross-functional delivery teams in consulting or enterprise solution environmentsMicrosoft Azure certifications related to data, analytics, or AI platforms preferredAbility to work with clients and internal teams to deliver solutions