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