{"id":2894668,"url":"https://alion.io/job/paypay-senior-data-scientist-credit-modeling","title":"Senior Data Scientist, Credit Modeling","company":{"id":328,"name":"PayPay","domain":"paypay.ne.jp","url":"https://alion.io/company/paypay","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":65,"open_postings":38,"ghost_share":0.5,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":103,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Databricks","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Python","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2023-11-14T10:36:30Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-30T03:51:50Z","board_verified":true,"closed_at":null,"days_open":1080,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":1079},"description":"About PayPay\nPayPay is a FinTech company that has grown to over 75M (as of August 2026) users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries.\nOUR VISION IS UNLIMITED_\nWe dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realize a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. We are looking for people who can embrace this challenge, refresh the product at breakneck speed and promote PayPay with professionalism and passion.\n※ Please note that you cannot apply or be selected in parallel with PayPay Corporation, PayPay Card Corporation and PayPay Securities Corporation.\n\nJob Description\nAs a Senior Data Scientist in PayPay Credit Modeling, you will lead work that improves credit risk and financial decisions.\nYou will lead modeling initiatives from identifying opportunities and framing ambiguous business problems through developing models, designing credible evaluations, and assessing real-world impact. You will collaborate closely with product, risk, data engineering, and machine learning engineering teams to translate research into reliable, scalable solutions.\nThis is a role with scope to shape the technical direction of modeling and analysis, coach colleagues, and influence decisions across PayPay.\nResponsibilities\nOwn the scientific approach to modeling work, from defining the decision and expected value through baselines, validation, and a clear recommendation.\nDevelop and evaluate models and features using large, varied datasets. Choose methods that fit the problem and can be explained, validated, and maintained.\nSet evaluation standards for how models will be used. Challenge assumptions, detect leakage and selection bias, account for delayed outcomes, and use appropriate baselines, time-aware tests, and calibration to judge whether results are reliable.\nEstimate likely effects on revenue, credit losses, exposure, portfolio quality, and customer outcomes. Make assumptions and uncertainty clear.\nGuide promising models through production with data and machine learning engineers. Define model and feature requirements, validate deployed behavior, monitor performance and outcomes, and recommend changes based on evidence.\nCommunicate findings and trade-offs to technical and non-technical stakeholders, and help teams decide whether to proceed, change course, or stop.\nLead technical discussions, critically review modeling approaches, mentor other data scientists, and establish reusable practices that improve the team's work.\nQualifications\nBachelor’s Degree in a quantitative field such as Computer Science, Mathematics, Statistics, Operations Research, Machine Learning or equivalent. An advanced degree is a plus.\nSubstantial professional experience in data science or applied machine learning, typically six years or more, with evidence of leading consequential modeling work from problem definition through production use and impact assessment.\nCore data science skills:Strong knowledge of statistical modeling, supervised learning, feature engineering, and model interpretation; sound judgment on when a simpler method is sufficient.\nPractical experience with validation and experimentation, including time-aware evaluation, calibration, bias or selection effects, and monitoring after deployment.\nAbility to work independently with large, imperfect datasets and distinguish a useful signal from leakage or artifacts.\n\nFinancial and decision skills:Ability to connect model outputs with financial and customer outcomes, and explain the trade-offs in a decision or policy.\nAbility to form a recommendation when evidence is incomplete, state its limits, and identify what would change the conclusion.\n\nCore technical skills:Strong hands-on Python and SQL skills for model development, data analysis, and reproducible work.\nExperience using common statistical and machine learning libraries such as scikit-learn or XGBoost.\nExperience working with large-scale data platforms or distributed data processing to develop features, train models, and evaluate results.\nExperience building reproducible analysis and model workflows, collaborating with engineering teams on deployment, and evaluating models after release.\nExperience building point-in-time features and reproducible model workflows, and working with engineering colleagues to deploy, monitor, and improve models in production.\n\nNice to have\nExperience in lending, banking, payments, or another financial decision domain. Credit risk and portfolio economics experience is especially valuable.\nExperience applying models to financial decisions, credit strategy, or portfolio optimization.\nExperience with causal inference, treatment effects, decision policy evaluation, or controlled experiments.\nHands-on experience with Databricks, Spark, BigQuery, or Amazon Redshift; experience with streaming tools such as Kafka or Amazon Kinesis is a plus.\nWays of working\nTake ownership of ambiguous questions and bring structure to the work needed to answer them.\nChallenge assumptions constructively and revise your view when the evidence changes.\nBalance speed with rigor, explainability, and the ability to maintain what you build.\nCommunicate trade-offs and decisions clearly to partners with different expertise and priorities.\nPayPay 5 senses\nPlease refer PayPay 5 senses to learn what we value at work.\nWorking Conditions \nEmployment Status\nFull Time\nOffice Location\nHybrid Workstyle※ You will be expected to work in the office, in alignment with organizational guidelines and team objectives.\n\nLIFE in JAPAN FACTBOOK\n\nWork Hours\nSuper Flex Time (No Core Time)\nIn principle, 9:00am-5:45pm (actual working hours: 7h45m + 1h break)\nHolidays\nEvery Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days\nPaid leave\nAnnual leave (up to 14 days in the first year, granted proportionally according to the month of employment. Can be used from the date of hire)\nPersonal leave (5 days each year, granted proportionally according to the month of employment)＊PayPay's own special paid leave system, which can be used to attend to illnesses, injuries, hospital visits, etc., of the employee, family members, pets, etc...\n\nSalary\nAnnual salary paid in 12 installments (monthly)\nBased on skills, experience, and abilities\nReviewed once a year\nLate overtime allowance※Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you\n\nBenefits\nSocial Insurance (health insurance, employee pension, employment insurance and compensation insurance)\n401K\nTranslation/Interpretation support\nVISA sponsor + Relocation support\nOther Information:\n PayPay Inside-Out (Corporate Blog) /JP\n PayPay Inside-out (Corporate Blog) /ENG\nPayPay Product Blog /JP\nPayPay Product Blog /ENG\n PIVOT動画：PayPayが仕掛ける金融革命","description_format":"text","description_chars":7123,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"Japanese","level":"Advanced (C1)","optional":false}]},"benefits":["401k plan","Annual leave","Health insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Payment Processing & Gateways"],"lifecycle":[{"event":"open","at":"2026-10-20T04:12:04Z"}],"visa":[],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.146,"p_room":0.28,"age_days":1080,"expected_fill_days":103,"reasons":["conf:1","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-30T05:48:23Z"},"pay":null,"html_url":"https://alion.io/job/paypay-senior-data-scientist-credit-modeling","json_url":"https://alion.io/job/paypay-senior-data-scientist-credit-modeling.json","meta":{"generated_at":"2026-10-30T06:26:28Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":8952,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-31T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":328},"rest":"https://alion.io/mcp/rest/get_company?id=328"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpaypay-senior-data-scientist-credit-modeling"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpaypay-senior-data-scientist-credit-modeling"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpaypay-senior-data-scientist-credit-modeling"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/paypay-senior-data-scientist-credit-modeling\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpaypay-senior-data-scientist-credit-modeling"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":2894668}},{"tool":"search_jobs","arguments":{"company":"paypay.ne.jp","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":2894668},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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