ICICI Securities - Data Analyst - SQL/Python

About The Role

We are seeking a highly motivated and detail-oriented Data Analyst to join our growing analytics team. You will play a key role in leveraging data to drive strategic decisions, solve complex business problems, and provide insights through dashboards and predictive models. The ideal candidate has a strong analytical background, a passion for working with data, and hands-on experience in Python, SQL, and data visualization tools like Tableau.

Key Responsibilities

• Analyze large datasets to identify trends, patterns, and insights that support business decision-making.
• Design and implement predictive and descriptive analytics models to solve real-world business use cases.
• Build and maintain interactive dashboards in Tableau to visualize KPIs and performance metrics.
• Conduct exploratory data analysis (EDA) to understand data characteristics and discover opportunities for improvement.
• Collaborate with cross-functional teams including product, marketing, operations, and engineering to gather requirements and deliver data-driven solutions.
• Deploy models or pipelines on AWS or Azure, and work on AI/ML-based use cases in cloud environments.
• Translate business questions into data analysis, present findings in a clear and concise manner.
• Ensure data quality, integrity, and governance across all analytics projects.
• Stay updated with the latest industry trends, tools, and techniques in data analytics and machine learning.
  
  

Requirements

Educational Background :

Bachelor's or Masters degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.

Technical Skills

• Proficient in Python for data analysis and machine learning.
• Strong experience in writing complex queries, data extraction, and transformation.
• Hands-on experience with Tableau or similar tools (e.g., Power BI, Looker).
• Experience developing and validating predictive analytics models.
• Familiarity with classification, regression, clustering, and other ML algorithms.
• EDA: Proven experience conducting exploratory analysis to uncover insights.
• Cloud Platforms: Working knowledge of AWS or Azure, especially in the context of data pipelines and machine learning services.
  
  

(ref:hirist.tech)