Data Analyst

Description About the Role We're looking for an analyst who thinks from first principles and builds things that last. You'll sit at the intersection of credit policy, product analytics, and growth — owning the pipeline from raw data to dashboards to the insights that improve decisions. This isn't a reporting role.

You'll partner directly with credit, product, and growth teams to diagnose funnel drop-offs, surface policy blind spots, and build the analytical infrastructure that makes better decisions the default. If you're early in your career but already thinking about the full stack — from data reliability to business impact — this is that seat. Key Responsibilities Write efficient, well-structured SQL queries and build views that power reporting and self-serve analytics across teams.

Develop and maintain Python scripts for data transformation, automation, and pipeline support. Own dashboards end-to-end — from data model to visualization — ensuring they're accurate, interpretable, and actually used. Collaborate with product, engineering, and business teams to define metrics, align on definitions, and keep data consistent across reporting layers.

Drive product analytics: track feature adoption, user behaviour, and funnel performance — and surface the signals that inform roadmap decisions. Build and iterate on predictive models for business use cases — activation likelihood, churn risk, user segmentation — and translate outputs into actionable recommendations. Take fragmented, unreliable data across multiple sources and consolidate it into a clean, trustworthy single source of truth.

Perform ad-hoc deep-dives and translate findings into clear recommendations for non-technical stakeholders. Support data validation and integrity checks as new pipelines and data sources come online. Qualifications & Skills 1–3 years of experience in analytics, BI, or a data-heavy role.

Strong, hands-on SQL — including query optimization, joins, and building views. Comfortable in Python for data wrangling, scripting, and automation. Experience working with at least one OLAP or columnar database (ClickHouse, Redshift, BigQuery, or similar).

Prior exposure to product analytics or a fintech/financial services environment. Proven ability to work across teams — you know how to ask the right questions, manage stakeholder expectations, and get alignment on data definitions. Strong communication skills: you can make a complex dataset land clearly with a non-technical audience.

Hands-on experience with bureau data (CIBIL, Experian, CRIF, or similar) — understanding pull-level data and deduplication challenges Nice to Have . Practical knowledge of Metabase: dashboard creation, advanced filtering, and enabling self-serve analytics. Familiarity with orchestration or transformation tools (dbt, Airflow).

An AI-native workflow — you use tools like Claude, Cursor, or Copilot to move faster and think sharper. About Us: Pice is a Banking & Financial Services (BFSI) company serving Indian SMEs. Pice has set out to make it easier for small businesses to get access to / use high-quality financial services.

We are building a suite of business-first products with payments & collections and combining it with powerful new credit products that businesses can use to grow to the next level. We are a vibrant team of 70+ people working across the domains of tech, product & business. Spearheaded by 3 dynamic founders, we are backed by Nexus Venture Partners, Paramark & 10 renowned Angels.