Data Analyst

Akaasa Technologies; Malvern (Chester County); On-site; USD 70,000 - 120,000; Full time

Job summary

Akaasa Technologies is seeking a Data Analyst to join its Analytics team. You will study transaction and portfolio data to uncover patterns and drive business strategy, including forecasting models for client behavior.

You will write SQL and Python to query data from Snowflake, BigQuery, and Redshift, build dashboards, and present insights to wealth advisors. The role emphasizes data governance and collaboration with data engineering.

Qualifications

• Advanced SQL with optimized queries, joins, subqueries, and window functions on large datasets.
• Proficiency in Python for data analysis and ML tasks.
• Experience with financial data and investment analytics is required.

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 ML algorithms to predict churn, net new assets, trade propensity, and lifetime value.
• Advanced Data Querying: Write efficient SQL queries and Python scripts to extract, transform, and analyze data across databases and cloud data warehouses (Snowflake, BigQuery, Redshift).
• Insights & Strategy Presentation: Translate findings into clear, actionable recommendations for leadership, portfolio managers, and wealth advisors.
• Dashboard & KPI Development: Design and maintain executive dashboards to track client metrics, trade volumes, and model performance.
• Data Governance & Integrity: Collaborate with Data Engineering and Data Governance to ensure data quality, compliance, and security.

Skills

SQL

Python

Financial investment securities domain

Tools

AWS Bedrock

AWS Glue

AWS S3

Job description

Data Analyst

assessment required

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:
  • SQL: Advanced capability in writing optimized queries, complex joins, subqueries, and window functions on large datasets.
  • Python: Proficiency with data analysis and machine learning libraries

Skills: Expert level SQL, Financial Investment Securities domain knowledge, Python, AWS services (e.g. Bedrock, Glue, S3)

Skills: Expert level SQL, Financial Investment Securities domain knowledge, Python, AWS services (e.g. Bedrock, Glue, S3)