Amount provides a unified digital origination and decisioning platform that helps financial institutions meet the moment. Designed to scale with banks and credit unions at any stage of their digital journey, Amount delivers a seamless, digital-first experience—streamlining everything from loan origination to deposit account opening. With built-in fraud orchestration and risk management, Amount enables financial institutions to control risk across any product while optimizing performance and enhancing security. Our flexible, modular platform is backed by enterprise-grade infrastructure and compliance, allowing institutions to launch new offerings in months, not years. Amount’s clients include financial institutions collectively managing over $3.1T in assets and serving more than 50 million U.S. consumers. Learn more at www.amount.com.
Inclusion, diversity, and belonging are core to Amount's values, and we believe they are more than words, they are actions. We support our commitment to these ideas by empowering intrepid engagement and learning, increasing diverse representation, and fostering a culture where everyone can bring their full self to work without regard to differences. We look for people who embrace this culture.
A DAY IN THE LIFE:
As a Data Analyst at Amount, your day will be dynamic and fast-paced. You'll start by collaborating with the Customer Success team to understand their data needs and priorities for the day. Your tasks may include analyzing customer performance and usage data, identifying trends or patterns, and generating insights to improve customer satisfaction and retention. You'll also work closely with the Revenue Operations team to ensure data accuracy and availability for analysis. You'll communicate your findings and recommendations to internal stakeholders, including Customer Success Managers and Leadership, as well as external stakeholders, to drive informed decision-making.
Team: Will join a team of ~40 across the Revenue Organization that includes Marketing, Sales, Sales Engineering, Solutions, Customer Success, and Operations.
Base Salary: $99,000 - $132,000
Benefits & Perks: Check them out HERE!
WHAT WE’LL TRUST YOU TO DELIVER:
- Analyze customer data to identify key trends, patterns, and insights that drive customer success metrics.
- Develop and maintain dashboards and reports to track customer health, usage patterns, and performance metrics.
- Collaborate with cross-functional teams, including Customer Success, Revenue Operations, Finance and Product, to gather requirements and implement data-driven solutions.
- Support Customer Success Managers with creating monthly and quarterly business reviews reports that create compelling data narratives.
- Proactively identify opportunities to optimize customer workflows and improve the overall customer experience.
- Provide ad-hoc analysis and support to address specific customer inquiries or challenges.
- Stay current with industry trends and best practices in data analysis and customer success to continuously enhance processes and methodologies.
WHAT YOU LIKELY BRING TO THE TABLE:
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
- Proven experience working as a data analyst, preferably in a customer-facing role within the fintech industry.
- Proficiency in SQL for data querying and manipulation.
- Strong analytical skills with the ability to interpret complex data sets and generate actionable insights.
- Experience with data visualization tools such as Tableau, Power BI, or Looker.
- Excellent communication skills, with the ability to present findings and recommendations to both technical and non-technical stakeholders.
- Detail-oriented mindset with a focus on data accuracy and quality.
- Ability to thrive in a fast-paced, collaborative environment and manage multiple priorities effectively.
Social Media: LinkedIn, Builtin, Twitter, Amount Blog
Tech Stack: Greenhouse, LinkedIn Recruiter, Lattice, G Suite, Atlassian, AWS, Python, Java, Ruby, GO, node.js, Temporal, Scala, Apache NiFi, Talend, Informatica, Hadoop, Hive, Spark, Pandas, Looker, Argo, Airflow Luigi, Kubernetes, C#, JavaScript (for advanced concepts), ASP.NET MVC, .NET Core, Microsoft SQL Server, Entity Framework (ORM for database interaction)
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