{"id":2513171,"url":"https://alion.io/job/zed-data-scientist","title":"Data Scientist","company":{"id":3904693,"name":"Zed","domain":"zed.co","url":"https://alion.io/company/zed-4","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Manila, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":13500,"max_usd":37000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":865},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Explainable AI","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-02-19T18:49:21Z","employer_posted_date":"2026-02-19","last_verified_at":"2026-10-16T10:58:25Z","board_verified":true,"closed_at":null,"days_open":238,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":238},"description":"About Zed\nZed is building the first AI-native, licensed neobank in the Philippines designed to democratize access to premium financial services for young professionals in global markets. The current banking system is broken, often shutting out the world’s youngest and fastest-growing consumer classes-we’re here to fix it.\nOur team is uniquely positioned to solve this. We are Stanford engineers and former YC founders who have spent our careers at the intersection of banking and hyper-growth startups like Square, Facebook, and Box. We’ve been here before, having previously built and exited Symple (YC W'17), a fast-growing B2B payments company.\nWe are backed by world-class investors, including Accel, Valar, Immad Akhund (Mercury), Dalton Caldwell (Y Combinator), and Kunal Shah (Cred).\nThe Role\nAs a Data Scientist at Zed, you will play a critical role in shaping how data and AI power our core financial products. In your first six months, you will own the development of data science and machine learning models that directly impact credit risk, decisioning, and product performance. You will work closely with Product, Risk, Engineering, and Finance partners to translate complex business problems into robust, production-ready data solutions in a fast-moving, resource-constrained startup environment.\nWhat You’ll Do\nBuild, validate, and iterate on machine learning models that support core financial use cases such as credit risk assessment, underwriting, and portfolio performance.\n\nPartner closely with cross-functional stakeholders-including Product, Risk, Engineering, and Finance-to understand business objectives, define success metrics, and deliver data-driven insights.\n\nTake end-to-end ownership of data science projects, from problem formulation, requirement setting, and data exploration to model development, evaluation, and handoff for production.\n\nLeverage modern AI techniques, including LLMs and generative AI workflows, to develop innovative solutions where appropriate (e.g., fine-tuning, RAG, or agentic systems).\n\nContinuously improve Zed’s data science practices by staying current with industry advancements and helping mature internal tools, processes, and standards.\n\nWhat You Bring\nExperience\n3+ years of professional experience in data science, machine learning, or applied AI, or equivalent graduate-level research with significant hands-on model development.\n\nDemonstrated experience building ML models from the ground up .\n\nTechnical Depth\nStrong proficiency in Python and common data science and ML libraries; experience with SQL and data analysis workflows.\n\nHands-on experience with machine learning model development and evaluation\n\nExposure to or experience with LLMs and generative AI, including fine-tuning, prompt engineering, RAG, or agentic systems.\n\nProblem-Solving & Communication\nExcellent analytical and problem-solving skills, with the ability to translate ambiguous business problems into structured data science solutions.\n\nStrong communication skills and comfort explaining technical concepts and results to non-technical stakeholders.\n\nEducation\nBachelor’s degree in a quantitative field such as data science, statistics, computer science, engineering, or equivalent practical experience. Advanced degrees are a plus.\n\nBonus (Nice-to-Haves)\nExperience in financial services, particularly credit risk modeling, scorecard development, or lending-related analytics.\n\nFamiliarity with advanced AI techniques such as causal inference, reinforcement learning, or explainable AI.\n\nExperience working in startups or constrained environments (e.g., small datasets, cold-start problems, limited resources).\n\nWe hire exceptional people from diverse backgrounds because different perspectives build better products.\nIf you’re excited about this role but don’t check every box, apply anyway. We value potential, ownership, and alignment with our values more than perfect résumés.\nWe are an equal opportunity employer and do not discriminate based on legally protected characteristics. We provide reasonable accommodations throughout the hiring process.\nCompensation includes salary, equity, and benefits. 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