🛠 Tech Stack

💼 About This Role

You'll join an AI-augmented delivery pod that builds data foundations for PE-backed companies. You'll move fluidly between messy source systems and production-ready pipelines, diagnosing data quality issues directly with clients. This role offers exposure to agentic-AI systems ahead of the market.

🎯 What You'll Do

• Build and maintain data pipelines from raw sources to production outputs
• Design and write custom ML models with feature engineering and deployment
• Explore unfamiliar datasets to identify structure and surface anomalies
• Diagnose data quality issues and drive resolution

📋 Requirements

• SQL and Python proficiency across data pipeline development
• Hands-on experience with machine learning workflows and modeling
• Experience working in fast-paced, sprint-based client-facing environments
• Background in finance or PE with ERP and FP&A data familiarity

✨ Nice to Have

• Experience with AI tools to accelerate data work
• Strong written communication for client-facing documentation

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 60 min

🚩 Heads Up

• High-velocity environment with short sprints and shifting requirements
• Requires client travel and direct client-facing work