Data Analyst (SQL / Python) | $15/hr Remote

Position: SwarmBench Task Engineer Data Analysis

Type: Short-Term Contract (4 weeks)

Compensation: $15 per hour

Location: Remote

Commitment: 30-40 hours per week with 4 hours overlap with PST

Role Responsibilities

• Design and author multi-agent benchmark tasks centered on complex data analysis workflows
• Create realistic synthetic datasets or curate real-world style datasets across domains such as finance, operations, security, or market analysis
• Build tasks that require agents to perform cross-referencing, anomaly detection, contradiction identification, and statistical computation across multiple sources
• Develop decomposition guides that split analytical work across specialist sub-agents such as financial, technical, security, or operations analysts
• Write precise oracle logic or verification scripts that validate specific analytical conclusions rather than generic summaries
• Create reproducible evaluation environments using Python and Docker
• Review task performance signals to ensure strong separation between weaker and stronger agentic systems
• Refine tasks to improve determinism, clarity, difficulty, and scoring quality

Requirements

• Strong years of experience in data analysis
• Strong proficiency in SQL and Python for data analysis and scripting (pandas, NumPy, or similar)
• Experience working with real-world, messy datasets such as CSV, JSON, logs, and reports
• Ability to design non-trivial analytical questions with clear, specific, and verifiable answers
• Solid understanding of statistical concepts including averages, distributions, outliers, and correlations
• Familiarity with AI coding benchmark environments (e.g., SWE-bench, Terminal-Bench)
• Comfortable with Docker including writing Dockerfiles, building images, and debugging container issues
• Ability to work independently in a remote environment

Application Process

• Apply/Easy Apply and check email for application form
• Fill Google form
• Assessment Link (After shortlisting to be completed within 24 hours)