Data Analyst

assessment required

hybrid malvern pa

About the Role

We are seeking a high-performing Data Analyst to join our Analytics team. In this role, you will play a pivotal part in unlocking value from massive volumes of transaction and portfolio data.

You will analyze client investment behaviors-such as buy/sell patterns, asset allocation shifts, and trading frequencies-to generate actionable insights that drive business strategy, enhance portfolio performance, and personalize client engagement. Furthermore, you will build and deploy predictive and forecasting models to help our advisors anticipate market opportunities and client needs.

Key Responsibilities

Investment Behavior & Transaction Analysis: Query and analyze large, complex financial datasets to identify patterns in client buying, selling, and asset allocation behaviors.

Predictive Modeling & Forecasting: Develop, validate, and maintain forecasting models and machine learning algorithms to predict client churn, net new assets (NNA), trade propensity, and client lifetime value.

Advanced Data Querying: Write efficient, complex SQL queries and Python scripts to extract, transform, and analyze data across diverse relational databases and cloud enterprise data warehouses (e.g., Snowflake, BigQuery, Redshift).

Insights & Strategy Presentation: Translate technical findings and statistical data into clear, compelling stories and actionable recommendations for executive leadership, portfolio managers, and wealth advisors.

Dashboard & KPI Development: Design and maintain executive dashboarding solutions to track key client metrics, trade volume trends, and predictive model performance over time.

Data Governance & Integrity: Collaborate with Data Engineering and Data Governance teams to ensure high standards of data quality, financial compliance, and security across all datasets.

Qualifications & Skills Required Qualifications

Technical Expertise:

o SQL: Advanced capability in writing optimized queries, complex joins, subqueries, and window functions on large datasets.

o Python: Proficiency with data analysis and machine learning libraries