Senior Data Scientist - PySpark/Azure Databricks

Job Position :

Years of Exp :

Mode of Working :

Technical Skills

• Strong hands-on experience with PySpark and Databricks data processing and modelling.
• Solid foundation in Regression modelling, statistical analysis, and model performance evaluation.
• Comfortable working with SQL systems and structured/unstructured data pipelines.
• Proficiency in Excel for quick analytical checks, and PowerPoint for developing clear, executive-friendly insights and presentations.
• Strong analytical mindset and exceptional problem-solving skills to translate data into actionable business strategies.
  

Good To Have Skills

• Exposure to pricing analytics or revenue management models (elasticity, discount simulations, price optimization).
• Fluency in retail domain terminologies and an understanding of business KPIs.
• Knowledge of data visualization tools such as Power BI or Tableau.
• Experience with Azure Databricks workflows or CI/CD-based deployment frameworks.
  

Soft Skills

• Excellent communication and storytelling abilities capable of simplifying complex analytics for non technical stakeholders.
• Demonstrated ability to mentor junior team members, review deliverables, and guide technical and analytical workstreams.
• Collaborative attitude with the ability to work cross-functionally across data, product, and business teams.
  

Key Responsibilities

• Design, develop, and optimize data processing and modeling pipelines using PySpark and Databricks.
• Build statistical and regression models to support business decision-making and performance optimization.
• Analyze structured and unstructured datasets to extract actionable insights and translate findings into clear business recommendations.
• Write complex SQL queries and manage end-to-end data workflows.
• Create concise analytical summaries using Excel and develop executive-level presentations using PowerPoint.
• Collaborate with cross-functional teams (Data Engineering, Product, Business) to understand business needs and deliver analytical solutions.
• Mentor junior data scientists, conduct code reviews, and oversee analytical workstreams.
• Ensure high-quality deliverables through strong problem-solving, critical thinking, and data storytelling abilities.