Senior Data Analyst (Python)

Role Overview We are seeking experienced SwarmBench task engineers — data analysis — to design and develop high-quality multi-agent benchmark tasks that evaluate the analytical reasoning, coordination, and execution capabilities of advanced AI systems. In this role, you will build realistic benchmark tasks that require AI agents to analyse large, messy, multi-source datasets, decompose work across specialist sub-agents, and arrive at specific, verifiable conclusions. These tasks may involve structured and semi-structured data such as CSVs, JSON files, logs, reports, survey results, vendor assessments, or financial and operational documents.

Your work will help measure how effectively AI systems perform complex analytical workflows involving cross-referencing, contradiction detection, anomaly identification, and statistical reasoning across multiple data sources. What does day-to-day look like Design and author multi-agent benchmark tasks centred 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 Contract Details: Duration: 12 months+ Pay: INR 1.75 L - 2.00 per month Number of positions: 12 Mode of work: Fully Remote Experience: 5+ Years Requirements 5+ 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 (CSV, JSON, logs, reports) Ability to design non-trivial analytical questions with clear, specific, and verifiable answers Solid understanding of statistical concepts (averages, distributions, outliers, correlations) Familiarity with AI coding benchmark environments (e.g., SWE-bench, Terminal-Bench) Comfortable working with Docker (writing Dockerfiles, building images, debugging containers) Additional Details Commitments Required: 8 hours per day with a 4-hour overlap with PST. Employment Type: Contractor position (Note: this role does not include medical/paid leave).