Sr. Data Analyst

Responsibilities

• Lead Analytics Projects: Independently gather requirements, identify relevant data, and write sophisticated SQL scripts to build data sets that enable you to generate insights through visualizations and presentations.

• Provide Analytics Support Across Business Functions: Deliver actionable insights for lifecycle marketing, business development, operations, product, and finance to drive strategic initiatives.

• Analyze Customer Transaction Behavior: Support analytics on customer transaction behavior, particularly for new product features and user adoption, to identify patterns and trends that align with business goals.

• Create Visualizations and Dashboards: Design impactful visualizations and automated dashboards to reveal key trends and measure the effectiveness of various initiatives, from marketing to product launches.

• Investigate Data Anomalies: Proactively investigate data anomalies and idiosyncrasies, uncovering underlying issues and opportunities that havent been explicitly requested.

• Exceed Partner Needs: Leverage your knowledge of the business to anticipate and exceed partner needs, using initial requirements as a foundation and building upon them with novel insights.

• Collaborate Across Teams: Work with internal and external stakeholders to define and deliver data, reports, visualizations, and dashboards critical to decision-making.

• Ensure Data Quality: Maintain high data quality through rigorous documentation and quality assurance processes.

• Drive Projects with Minimal Guidance: Take ownership and accountability for meeting contribution goals, consistently pushing projects forward independently.

• Required Qualifications:

• Bachelors Degree in engineering, economics, physics, or a related quantitative discipline.

• 4+ years of data analytics experience, ideally within a financial services or business analytics context.

• Advanced SQL proficiency, including expertise with window functions, common table expressions (CTEs), performance tuning, and query optimization for large data sets.

• Proven experience working with cross-functional data in marketing, product, finance, or operations.

• Experience with data visualization and dashboard creation using tools such as MicroStrategy, Tableau, Power BI, Looker, QuickSight, or Excel.

• Familiarity with statistical methods and experience using R or Python for in-depth data analysis.

• Proactive Mindset: A natural problem-solver who identifies and investigates data inconsistencies or patterns, uncovering insights that drive business impact.

• Strong communication skills, with the ability to explain complex analyses to both technical and non-technical stakeholders.

• Excellent organizational and problem-solving skills, capable of transitioning from detailed analysis to high-level strategic insights.

• Ability to influence and drive alignment through constructive dialogue without formal authority.

• Flexibility in prioritizing tasks, selecting appropriate tools, and managing multiple projects with competing priorities.

• Strong relationship-building skills and a desire to collaborate in a high-energy, team-oriented environment.

• Financial Transaction Data Analysis: Experience in analyzing and mining financial transaction data for insights, with an understanding of payment technologies, payment types, credit/debit card networks, and purchase authorization/settlement processes.

• Data Science and Modeling: Experience in building and deploying predictive models (regression, classification, clustering, time series forecasting) using Python, R, or similar tools.

• Machine Learning: Familiarity with machine learning algorithms and their application in deriving insights from large datasets.

• Cross-Functional Analytics Expertise: Experience working on projects across multiple business areassuch as marketing, product, finance, and operationstranslating data into actionable business insights.