Data Analyst

About the Role

Pice is seeking an analytical professional who approaches challenges from first principles and is dedicated to building lasting solutions. In this pivotal role, you will operate at the nexus of credit policy, product analytics, and growth initiatives, taking ownership of the entire data pipeline, from raw data to insightful dashboards that drive informed decision-making. This is more than a reporting position; you will collaborate directly with credit, product, and growth teams to dissect funnel drop-offs, identify policy blind spots, and establish the analytical infrastructure that promotes better decision-making as the standard. If you are an early-career professional who already considers the full spectrum of data – from reliability to business impact – this opportunity is for you.

Key Responsibilities

• Develop and maintain efficient, well-structured SQL queries and views to support reporting and self-serve analytics across various teams.
• Create and manage Python scripts for data transformation, automation, and pipeline maintenance.
• Lead the end-to-end ownership of dashboards, encompassing data modeling and visualization, ensuring accuracy, interpretability, and active usage.
• Partner with product, engineering, and business teams to define key metrics, establish consistent definitions, and maintain data integrity across reporting layers.
• Drive product analytics by tracking feature adoption, user behavior, and funnel performance, surfacing critical signals to inform product roadmap decisions.
• Develop and refine predictive models for key business use cases, such as activation likelihood, churn risk, and user segmentation, translating model outputs into actionable recommendations.
• Consolidate fragmented and unreliable data from multiple sources into a clean, trustworthy, and unified source of truth.
• Conduct in-depth ad-hoc analyses and translate findings into clear, concise recommendations for non-technical stakeholders.
• Support data validation and integrity checks as new pipelines and data sources are implemented.

Qualifications & Skills

• 1 to 3 years of experience in analytics, Business Intelligence (BI), or a data-intensive role.
• Proficiency in SQL, including query optimization, complex joins, and view creation.
• Experience with Python for data manipulation, scripting, and automation tasks.
• Hands-on experience with at least one OLAP or columnar database such as ClickHouse, Redshift, BigQuery, or similar.
• Prior exposure to product analytics or experience within the fintech/financial services sector.
• Demonstrated ability to collaborate effectively across teams, adept at asking pertinent questions, managing stakeholder expectations, and achieving alignment on data definitions.
• Strong communication skills, with the ability to clearly convey complex datasets to non-technical audiences.
• Practical experience with bureau data (e.g., CIBIL, Experian, CRIF), including an understanding of pull-level data and deduplication challenges.

Nice to Have

• Practical knowledge of Metabase, including dashboard creation, advanced filtering, and enabling self-serve analytics.
• Familiarity with data orchestration or transformation tools like dbt or Airflow.
• Experience leveraging AI tools (e.g., Claude, Cursor, Copilot) to enhance productivity and analytical thinking.