Front-Facing Data Analyst

Plat.AI; Glendale (CA); On-site; USD 85,000 - 120,000; Full time

Job summary

Plat.AI in Glendale, CA seeks a Front-Facing Data Analyst to bridge our data science team and external stakeholders. You will translate complex data into actionable business insights, build dashboards, and present findings to clients and executives.

You will own analytics engagement, conduct A/B tests, monitor KPIs, and collaborate with underwriting, marketing, risk, and engineering to optimize performance in fintech lending contexts.

Qualifications

• Bachelors degree in Statistics, Mathematics, Economics, Computer Science, or related.
• 25+ years of experience in data analytics, preferably fintech or lending.
• Strong proficiency in SQL.
• Experience with R or Python.
• Experience with BI tools (Tableau, Looker, etc.).
• Excellent communication and presentation skills.
• Ability to explain technical concepts to non-technical audiences.

Responsibilities

• Serve as the primary analytics point of contact for clients and external stakeholders.
• Present performance reports, dashboards, and model insights to clients and executives.
• Translate complex statistical results into clear business recommendations.
• Participate in strategy calls and coordinate with underwriting, marketing, risk, and engineering teams.
• Analyze large datasets to identify trends, risks, and opportunities.
• Build and maintain dashboards (Tableau, Looker, Power BI, etc.).
• Monitor KPIs such as approval rates, conversion, fraud indicators, and portfolio performance.
• Perform root cause analysis on performance shifts and run A/B tests.
• Work with data scientists to interpret model outputs.
• Identify segments with low performance and recommend optimization strategies.

Skills

SQL

Python

R

Data visualization

Communication

Presentation skills

Analytical thinking

Fintech domain knowledge

Education

Bachelors degree in Statistics, Mathematics, Economics, Computer Science, or related

Tools

Tableau

Looker

Job description

We are seeking a highly analytical and business-savvy Front-Facing Data Analyst to serve as

the bridge between our data science team and external stakeholders. This role combines strong technical data skills with client communication, strategic insight, and performance optimization expertise.

The ideal candidate is comfortable analyzing complex datasets, translating findings into actionable insights, and presenting results directly to clients, partners, and executive teams.

Key Responsibilities

Client & Stakeholder Engagement

• Serve as the primary analytics point of contact for clients
• Present performance reports, dashboards, and model insights
• Translate complex statistical results into clear business recommendations
• Participate in strategy calls
• Analyze large datasets to identify trends, risks, and opportunities
• Build and maintain dashboards (Tableau, Power BI, Looker, etc.)
• Monitor KPIs such as approval rates, conversion, fraud indicators, and portfolio performance
• Segment performance by channel, risk tier, geography, or campaign
• Perform root cause analysis on performance shifts
• Work alongside data scientists to interpret model outputs
• Conduct A/B testing and performance experiments
• Identify segments with low performance and recommend optimization strategies
• Coordinate with underwriting, marketing, risk, and engineering teams
• Assist in translating business requirements into analytical frameworks
• Support compliance and reporting needs where applicable

Required Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or related
• field
• 2–5+ years of experience in data analytics, preferably in fintech or lending
• Strong proficiency in SQL
• Experience with R or Python
• Experience with BI tools (Tableau, Looker, etc.)
• Excellent communication and presentation skills
• Ability to explain technical concepts to non-technical audiences

Preferred Qualifications

• Experience with underwriting analytics or credit risk modeling
• Familiarity with interpretable ML models (scorecards, gradient boosting, etc.)
• Knowledge of fraud detection metrics
• Experience working in a client-facing or consulting environment

Core Competencies

• Strong analytical thinking
• Business acumen
• Detail-oriented but able to see big picture