Data Scientist

What You'll be doing: Develop, implement, and deploy machine learning models to solve real-world business problems at scale. Design statistical forecasting and optimization models to support business planning and decision-making. Ingest and process large volumes of data from APIs, databases, and structured/unstructured sources. Perform data transformation, feature engineering, and advanced analytics using PySpark and SQL on Databricks. Leverage MLflow for model tracking, versioning, and deployment. Collaborate with stakeholders to translate complex business requirements into actionable data science solutions. Apply appropriate statistical and machine learning methods based on the nature of data and business objectives. Communicate findings clearly and effectively to both technical and non-technical audiences. Requirements: 8–10 years of experience in data science or related fields. At least 4 years of hands-on experience as a Data Scientist in real-world production environments. Minimum of 2 years experience working with Azure Cloud, including Databricks, Azure Data Factory (ADF), and Moldflow. Strong programming skills in Python and PySpark. Proven experience in building and scaling machine learning and forecasting models. Experience designing and implementing optimization algorithms and advanced statistical models. Familiarity with Natural Language APIs and modern ML toolkits. Excellent communication and storytelling skills, with the ability to present technical concepts to business users. Demonstrated ability to independently solve problems and drive data science initiatives end-to-end. Technical Skill Set Languages & Tools: Python, PySpark, SQL Cloud & Frameworks: Azure, Databricks, Azure Data Factory, MLflow ML & Analytics: Machine Learning, Forecasting, Optimization, Natural Language APIs Others: Strong analytical mindset, data storytelling, stakeholder collaboration