Data Solutions & Analytics Senior Analyst

Match Point Solutions•Chandler, AZ
•Remote

About The Position

As a Senior Data Analyst on the Brokerage Risk Data Solutions and Analytics team, you will collaborate with Operations, Compliance, Product, and Engineering teams to improve efficiency, scalability, and risk management for broker-dealer operations. The role focuses on building dashboards, performing in-depth analysis, and developing data-driven solutions using data pipelines, artificial intelligence, and large language models (LLMs) to optimize workflows.

Requirements

  • At least 5 years of experience in data analytics, data engineering, or a related technical role, with a history of delivering impactful data solutions.
  • Expertise in SQL and Python for data analysis, process automation, and ETL pipeline development.
  • Proficiency in building dashboards and data visualizations, with experience in tools such as Superset and Tableau; developer experience is preferred.
  • Ability to apply statistical analysis methods to uncover insights, identify patterns, and inform strategic initiatives.
  • Ability to work effectively with cross-functional teams, communicate clearly, and translate complex data into actionable insights.
  • Interest in exploring and applying emerging technologies, including generative AI and large language models (LLMs), to optimize processes and workflows.

Nice To Haves

  • Experience using Databricks.
  • Experience with Tableau or Superset in a developer capacity.

Responsibilities

  • Partner with Operations, Compliance, Product, and Engineering teams to understand business challenges and deliver data-driven solutions.
  • Build and maintain scalable data pipelines using Python, Spark, and Airflow to automate processes such as key risk indicators, detective controls, risk alerts, reconciliations, and reporting.
  • Develop solutions using generative AI and large language models (LLMs) to streamline processes and improve operational workflows.
  • Develop user-friendly dashboards to monitor products, systems, and business processes.
  • Transform complex data into clear visualizations that inform partners and support decision-making.
  • Perform exploratory data analysis to identify actionable insights and inform strategies for mitigating risks and improving operational efficiency.
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