Summary

About the team + role

As a Senior Data Analyst on the Brokerage Risk Data Solutions and Analytics team, you’ll collaborate with operations, compliance, product, and engineering teams to enhance efficiency, scalability, and risk management for our broker-dealer operations. This role focuses on building dashboards, performing deep analysis, and developing data-driven solutions incorporating data pipelines and use of AI and large language models (LLMs) to optimize workflows.

The role is located in the office location(s) listed on this job description which will align with our in-office working environment. Please connect with your recruiter for more information regarding our in-office philosophy and expectations.

What you’ll do

Collaboration and Stakeholder Engagement

1. Partner closely with Operations, Compliance, Product, and Engineering to understand business challenges and deliver impactful, data-driven solutions.

Operational Efficiency and Process Optimization

1. Build and maintain scalable data pipelines using Python, Spark and Airflow to automate critical processes, such as key risk indicators, detective controls, risk alerts, reconciliations, and reporting.
2. Develop solutions that leverage Generative AI and large language models (LLMs) to streamline and optimize processes, driving innovation in operational workflows.

Data Visualization and Reporting

1. Develop meaningful, user-friendly dashboards to monitor the health of products, systems, and business processes.
2. Transform complex data into clear and insightful visualizations to inform partners and drive decision-making.

Exploratory Data Analysis and Risk Mitigation

1. Perform exploratory data analysis to uncover actionable insights and inform data-driven strategies for mitigating risks and optimizing operational efficiencies.

What you bring

1. 5+ years of experience in data analytics, data engineering, or a related technical role with a strong history of delivering impactful data solutions.
2. Demonstrated expertise in SQL and Python for data analysis, process automation, and developing ETL pipelines. Experience using Databricks is a plus.
3. Proficient in building intuitive dashboards and data visualizations, with experience in tools like Tableau, Looker, or Superset (preferably in a developer capacity).
4. Proven ability in statistical analysis methods to uncover insights and identify patterns and translate complex data into actionable insights..
5. Enthusiasm for exploring and leveraging emerging technologies, such as Generative AI and large language models (LLMs), to optimize processes and enhance workflows.

Skills

• Analytical Thinking
• Development
• Python
• SQL