Got it! I've searched for Senior Data Analyst roles in New York within the banking industry, with a salary starting at $90,000, requiring 3-5 years of experience, and proficiency in SQL, Python, and data visualization tools. I found 57 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Senior BSA Data Analyst at Alma Bank is fundamentally tasked with utilizing data to support business decisions within the BSA department. This role demands not only a high level of technical proficiency in data analysis tools but also strong analytical thinking to identify trends and anomalies that could impact the bank's operations and compliance. The key responsibilities revolve around collecting, cleaning, and analyzing large datasets, and effectively communicating findings to both technical and non-technical stakeholders. Candidates will face challenges such as ensuring data quality and overcoming potential ambiguities in stakeholder requirements. Success in this position is likely characterized by the ability to provide actionable insights that lead to informed strategic decisions and operational improvements. High performing analysts will be adept at balancing technical execution with compelling storytelling through data visualizations, fostering collaboration with various teams, and continuously refining methodologies to enhance data analysis processes.

Company Analysis:

Alma Bank operates as a community bank in a competitive metropolitan landscape, characterized by a strong focus on customer service and personalized banking solutions. This positioning as a mid-sized, customer-oriented bank suggests that the Senior BSA Data Analyst's role is pivotal in enhancing internal processes which directly impact customer experiences and compliance with financial regulations. The culture at Alma Bank appears to emphasize collaboration and continuous improvement, aligning well with the responsibilities of the Data Analyst role that involves working closely with cross-functional teams. This role is not positioned as a mere support function but is integral to the strategic objectives of the bank, particularly in compliance and risk management areas, which are increasingly critical in today's banking environment. There is an opportunity for visibility within leadership as data-driven insights will drive more significant business decisions.

Absolutely. Here are some mock interview questions that could come up:

• Can you describe a time when you identified a key trend in data that significantly influenced a business decision?
• Tell me about a challenging dataset you had to clean and analyze. What steps did you take to overcome the difficulties?
• Explain how you would communicate complex data findings to a non-technical audience.
• Describe a situation where you had to collaborate with diverse teams to achieve a common goal. What was your approach?
• How would you approach gathering requirements for a new data analysis project from a variety of stakeholders?
• What statistical methods do you believe are the most important for analyzing banking data, and why?
• Can you walk us through a project where you utilized tools like SQL or Python for data analysis? What were the key outcomes?
• Imagine you discover an anomaly in transaction data that could indicate potential financial crime. How would you investigate and report this finding?
• Why are you interested in working at Alma Bank specifically, and how does that align with your career goals?
• What aspects of our company culture do you believe resonate most with your work style and professional values?
• Given Alma Bank's focus on customer service, how would you ensure that your data recommendations support our mission of personalized banking?
• If hired, what would your initial 30-60-90 day plan look like in terms of impact and contributions to the team?
• What questions do you have about our data analytics processes or technologies that we currently use?
• How do you stay updated with the latest trends and tools in data analysis, and how would you apply that knowledge here?
• What improvements would you suggest for our current data collection and aggregation methodologies based on your experience?