About the role
Responsibilities Own the enrichment and signal layer of MAGNiTT's data to create new value Build benchmarking engines for MENA fund performance (TVPI, DPI, IRR) Develop proxies, estimates, and derived calculations for revenue and valuation Apply AI and LLM-assisted extraction to automate manual workflows Build and maintain Python scripts for data collection and cleaning Monitor automated pipelines for errors or drift Query internal databases using SQL to validate automation logic Requirements 3+ years in data science, quantitative analysis, or applied data engineering Strong Python skills (pandas, NumPy, scraping, parsing)\n- Advanced SQL knowledge (complex joins, window functions) Solid grounding in statistics and modeling Experience designing derived metrics and proxies Hands-on experience with entity resolution or record matching Practical experience applying LLMs or AI tools to data extraction Product-minded approach to turning datasets into new metrics Preferred Qualifications Experience using LLMs for information extraction or classification Familiarity with the venture capital or private capital ecosystem Experience with Tableau or similar BI tools Benefits Hybrid working structure Remote working policies Visa and insurance Leave increment based on tenure Learning platforms and career growth