Lead impactful projects at a dynamic investment firm, enhancing portfolio analytics and strategy insights. Collaborate across teams to drive innovation and deliver actionable intelligence. Develop expertise in financial tools and methodologies.
Associate Portfolio Analytics Strategy Specialist
in Financial Services PermanentJob Detail
Job Description
Overview
- Provide actionable portfolio insights and analytics to portfolio managers, leadership, and client-facing teams.
- Transform complex data into meaningful analysis for portfolio construction and performance evaluation.
- Collaborate with investment, risk, sales, and marketing teams to deliver impactful insights.
- Support portfolio construction, positioning, and strategy analysis for various investment vehicles.
- Develop and enhance portfolio analytics tools and reporting templates for improved workflows.
- Conduct quantitative and qualitative analysis of performance, exposures, and portfolio characteristics.
- Prepare materials and summaries for portfolio managers and client reviews.
- Contribute to firm-wide strategic initiatives through analytics and insights.
Key Responsibilities & Duties
- Serve as the dedicated analytics specialist for assigned equity strategies.
- Develop a deep understanding of investment objectives, guidelines, and risk exposures.
- Conduct quantitative analysis of performance attribution and style/factor exposures.
- Prepare dashboards, reports, and presentations for internal and external stakeholders.
- Collaborate with cross-functional teams to support product development and investor communications.
- Enhance reporting processes and adopt best practices for analytics delivery.
- Mentor junior associates and ensure quality in deliverables.
- Investigate performance-related issues and ensure data accuracy across analytics tools.
Job Requirements
- Bachelor's degree in business, finance, or a quantitative field such as statistics or engineering.
- 3-6 years of experience in portfolio analytics, equity research, or risk analysis.
- Proficiency in financial applications like FactSet PA, Morningstar Direct, and Bloomberg.
- Knowledge of programming languages such as Python, SQL, or R for data manipulation.
- Strong analytical and quantitative skills with proficiency in financial modeling and statistical analysis.
- Exceptional communication skills to present complex concepts to diverse audiences.
- Advanced knowledge of Microsoft Excel, VBA, PowerPoint, and Word.
- Highly proactive, self-motivated, and committed to continuous learning and development.
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