Full-Time Data Analyst Senior

The Data Analyst will support ongoing projects focused on data accuracy, consumer advocacy, and related analytics. You will handle complex analytic requests and collaborate with partners to identify opportunities for improving data quality and data delivery.

Main Responsibilities

1. Analyze complex data trends across consumer, commercial, housing, and alternative credit data to create insights that inform strategic decisions.
2. Deploy analytical workflows, scalable data pipelines, data science solutions, and machine learning models to enhance data quality and operational efficiency.
3. Translate high-level requirements into clear technical specifications, data models, and process flow diagrams that support solution development.
4. Communicate analytical findings through compelling storytelling, data visualizations, and executive-level presentations to guide partner decision-making.
5. Collaborate with internal clients to assess and resolve data quality issues, offering expert guidance as part of established data remediation programs.
6. Partner with teams including Data Ops, Product Development, Compliance, and Audit to gather insights and feedback that shape data-driven programs and product strategies.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Applied Mathematics, or a related quantitative field; or equivalent practical experience.
• 5+ years of experience in analytics, SQL, and proficient in relational and distributed data systems such as Aurora, MySQL, Hive, Athena.
• Experience analyzing large datasets using tools like Alteryx, Python, SAS, R, AWS Glue.
• Experience building and delivering insights through data visualization and BI tools such as Tableau, Power BI, Qlik, and Microsoft Excel (can write advanced macros) (can maintain complex spreadsheets)/PowerPoint.
• Deep interest in data modeling, machine learning, or GenAI, and proficiency in tools such as Python (NumPy, pandas, scikit-learn, TensorFlow, PyTorch) and Spark.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform (GCP).
• Prior experience in the consumer credit, lending, or financial services industry.
• Knowledge of data domains such as CRRG/Metro2 standards, public records, credit inquiries, and commercial credit data.

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