Pice®
Website:
piceapp.com
Job details:
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.
Nice to Have
- Hands-on experience with bureau data (CIBIL, Experian, CRIF, or similar) — understanding pull-level data and deduplication challenges.
- 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.
Click on Apply to know more.