Senior Business Analyst

We are seeking a highly skilled and motivated Senior Analyst to join our Investment Analytics team. The ideal candidate will have 4 - 6 years of experience in financial analytics, with strong proficiency in Python, Power BI, and SQL. This role involves working closely with investment strategists, portfolio managers, and data engineers to deliver actionable insights and support data-driven decision-making across the banks investment portfolios.Key Responsibilities :- Develop and maintain analytical models to support investment decision-making and portfolio optimization.- Design and automate dashboards and reports using Power BI to visualize key investment metrics and trends.- Write efficient SQL queries to extract, transform, and analyze large datasets from multiple sources.- Use Python for advanced analytics, including statistical modeling, forecasting, and scenario analysis.- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.- Monitor market trends, macroeconomic indicators, and portfolio performance to identify risks and opportunities.- Ensure data integrity, accuracy, and consistency across all analytics outputs.- Present findings and recommendations to senior stakeholders in a clear and compelling manner.Required Skills & Qualifications :- Bachelors or Masters degree in Finance, Economics, Statistics, Computer Science, or a related field.- 4 - 6 years of experience in investment analytics, financial modeling, or data analysis within the banking or financial services industry.- Strong hands-on experience with Python , Power BI, and SQL.- Solid understanding of investment products, portfolio theory, and financial markets.- Experience with data visualization, storytelling with data, and executive-level reporting.- Excellent problem-solving skills and attention to detail.- Strong communication and stakeholder management skills.Preferred Qualifications :- Experience with cloud platforms (e.g., Azure, AWS) and data pipelines.- Knowledge of machine learning techniques and their application in finance.- Familiarity with regulatory requirements and risk analytics. (ref:hirist.tech)