Role Overview:
As a Data Analyst for Insights & Operational Excellence at MMF, your main responsibility will be to collaborate closely with Finance and other cross-functional stakeholders. You will drive data-informed decision-making and operational efficiency through code-first, scalable solutions. Your role will involve identifying key challenges within Finance operations and designing, developing, and maintaining Python-based automations, data pipelines, and analytics solutions. Leveraging cloud technologies such as Microsoft Azure and database systems, along with emerging AI capabilities, including foundational knowledge of LLMs and generative AI, you will deliver efficient and future-ready digital solutions to enhance business outcomes.

Key Responsibilities:
- Design, develop, and maintain Python-based automations and data processing solutions to transform raw data into actionable business insights.
- Develop efficient, reusable, and well-documented code to support analytics, automation, and operational excellence initiatives.
- Write and optimize SQL queries involving multi-table joins to support data analysis and downstream applications.
- Work with relational and cloud-based databases to ensure data quality, performance, and reliability.
- Leverage Microsoft Azure services for data storage, analytics, automation, and integration of end-to-end solutions.
- Apply basic AI and machine learning concepts to enhance analytics and automation capabilities.
- Demonstrate strong analytical and creative problem-solving skills to address complex business challenges.
- Collaborate effectively with cross-functional stakeholders, demonstrating strong interpersonal, communication, and analytical skills.

Qualifications Required:
- 24 years of relevant experience in data analytics, including Python-based data analysis and exposure to cloud platforms such as Microsoft Azure.
- Hands-on experience with SQL and relational databases is required. Basic exposure to AI/ML concepts or applied analytics.
- Knowledge of Python for data analysis and automation (e.g., pandas, numpy).
- Basic understanding of AI and machine learning concepts and applied analytics.
- Familiarity with SQL and relational database fundamentals (Oracle, Snowflake, or similar).
- Working knowledge of Microsoft Azure (data storage, analytics, or integration services).
- Experience with Alteryx or Dataiku for data preparation and transformation.
- Prompt Engineering skills.

• Please Note: The JD does not contain any additional details about the company.* Role Overview:

As a Data Analyst for Insights & Operational Excellence at MMF, your main responsibility will be to collaborate closely with Finance and other cross-functional stakeholders. You will drive data-informed decision-making and operational efficiency through code-first, scalable solutions. Your role will involve identifying key challenges within Finance operations and designing, developing, and maintaining Python-based automations, data pipelines, and analytics solutions. Leveraging cloud technologies such as Microsoft Azure and database systems, along with emerging AI capabilities, including foundational knowledge of LLMs and generative AI, you will deliver efficient and future-ready digital solutions to enhance business outcomes.

Key Responsibilities:
- Design, develop, and maintain Python-based automations and data processing solutions to transform raw data into actionable business insights.
- Develop efficient, reusable, and well-documented code to support analytics, automation, and operational excellence initiatives.
- Write and optimize SQL queries involving multi-table joins to support data analysis and downstream applications.
- Work with relational and cloud-based databases to ensure data quality, performance, and reliability.
- Leverage Microsoft Azure services for data storage, analytics, automation, and integration of end-to-end solutions.
- Apply basic AI and machine learning concepts to enhance analytics and automation capabilities.
- Demonstrate strong analytical and creative problem-solving skills to address complex business challenges.
- Collaborate effectively with cross-functional stakeholders, demonstrating strong interpersonal, communication, and analytical skills.

Qualifications Required:
- 24 years of relevant experience in data analytics, including Python-based data analysis and exposure to cloud platforms such as Microsoft Azure.
- Hands-on experience with SQL and relational databases is required. Basic exposure to AI/ML concepts or applied analytics.
- Knowledge of Python for data analysis and automation (e.g., pandas, numpy).
- Basic understanding of AI and machine learning concepts and applied analytics.
- Familiarity with SQL and relational database fundamentals (Oracle, Snowflake, or similar).
- Working knowledge of Microsoft Azure (data storage, analytics, or integration services).
- Experience with Alteryx or Dataiku for data preparation and transformation.