Business Risk Analytics

Department

Minimum Managerial Experience

Preferred

Responsibilities:

Lead the overall data analysis and business intelligence strategy, ensuring alignment with company goals and objectives.

Develop and execute a roadmap for data analytics, visualization, and reporting across various business functions.

Establish and maintain best practices for data analysis, reporting, and data-driven decision-making.

Ensure proper data governance, including data accuracy, integrity, security, and compliance with industry standards.

Leverage data analytics tools (e.g., Power BI, SQL, Python) to gather, manipulate, and analyze business data to identify risk trends and patterns.

Manage and optimize data infrastructure, ensuring scalability, performance, and reliability.

Utilize advanced analytical techniques (e.g., Python) to drive deeper business insights and provide predictive models to optimize business strategies.

Provide actionable, data-driven recommendations to senior leadership and stakeholders, supporting critical business decisions.

Develop executive-level dashboards, reports, and visualizations, translating complex data into actionable insights.

Serve as a trusted advisor to senior leadership, providing strategic insights and recommendations based on data analysis.

Collaborate with business units to define KPIs, set benchmarks, and measure performance.

Establish relationships with external partners and vendors to implement new technologies and solutions where necessary.

Stay at the forefront of new data technologies, industry trends, and best practices to ensure the organization remains competitive.

Drive continuous improvement initiatives, enhancing reporting efficiency, accuracy, and business impact.

Well versed with financial or Business terms.

Technical Skills:

Expertise in Power BI, including advanced dashboard development, data modeling, and visualization techniques.

Strong experience in Python, leveraging it for data manipulation, automation, and advanced analytics

Advanced proficiency in SQL, with experience writing complex queries, creating ETL processes, and managing data pipelines.