{"id":871406,"url":"https://alion.io/job/flinks-senior-data-scientist","title":"Senior Data Scientist / Scientifique de données senior","company":{"id":58125,"name":"Flinks","domain":"flinks.com","url":"https://alion.io/company/flinks","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Montreal, Canada"],"countries":["CA"],"hiring_countries":["CA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":72000,"max_usd":138000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure DevOps","optional":false},{"name":"BERT","optional":false},{"name":"CI/CD","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubeflow","optional":false},{"name":"MLFlow","optional":false},{"name":"NER","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-09-04T00:00:00Z","employer_posted_date":"2026-09-04","last_verified_at":"2026-11-06T02:14:30Z","board_verified":true,"closed_at":null,"days_open":63,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":62},"description":"About Flinks\nFlinks is the embedded finance platform that brings together connectivity, intelligence, and payments - giving businesses the infrastructure they need to build and deliver seamless financial experiences at scale.\nAs a leader in Open Finance in Canada, we’ve grown since 2016 into one of North America’s most trusted platforms for financial data access, enrichment, and money movement. We work with innovators across many industries, including lending, fintech, banking, insurance, and wealth management.\nToday, our platform connects to 15,000+ financial institutions across North America and powers over 1M monthly connections. We also give our customers unprecedented visibility into 4,500+ real-time financial insights to support smarter decisioning. Companies rely on Flinks to streamline onboarding, verify income, assess credit risk, and power faster payment experiences.\nWe’re on a mission to drive financial innovation and help businesses build financial experiences that feel effortless, connected, and customer-first. That’s where you come in.\nThe Role\nWe're hiring a Senior Data Scientist to own machine-learning models end to end - from framing the problem and designing the model through the training pipeline, deployment to a live endpoint and the model-quality monitoring that keeps it accurate in production. This is a hands-on, engineering-heavy data-science role: you build and ship your own models.\nWhere this role sits: you own the models and their quality. Our Data Engineering function owns the shared data platform and serving infrastructure you build on - the warehouse, pipelines, governance, CI/CD and the operational reliability of the serving endpoints - so you stay focused on the science and the model lifecycle, not on running the platform.\nWe're explicit about this because it matters: if you're looking for a pure research or notebook-only role, this isn't it. If you're energized by taking a model all the way to a live, monitored endpoint and seeing it drive real financial decisions - you'll thrive here.\nWe're not building ML for ML's sake: we judge models by the business outcomes they move - risk reduction, enrichment accuracy, customer adoption, operational efficiency, revenue and connecting your model improvements to those outcomes is part of the role.\nWhat You'll Do\nOwn ML models end to end - frame the problem, write the design/RFC, build and train the model, ship it to a served endpoint and monitor its quality in production.\nBuild your model's training pipeline and package it for serving, deploying onto the shared platform Data Engineering builds and operates.\nOwn model quality, not the platform - you watch drift and performance and decide when to retrain.\nEvaluate rigorously - experimental design, statistical validation, drift detection and retraining, champion-challenger evaluation and promotion.\nPartner across the org - your model outputs feed the attributes/enrichment layer, payments risk, dashboards and client integrations, you'll collaborate with Data Engineering, backend, product and QA on contracts, deployment and rollout.\nMove fast with AI-assisted development -we use it to accelerate implementation and experimentation, the highest-leverage contribution in this role comes from strong problem framing, system design, evaluation rigor and clear technical specifications.\nWhat You'll Work On\nA few of the live ML systems this role owns end to end:\nTransaction categorization - a hierarchical, multi-task BERT classifier running as segment based models, trained on labelled data with synthetic top-ups for rare classes.\nReversal / \"final-category\" detection - a hybrid ML + analytical-rule model classifying reversal types and linking each back to its original debit, promoted via champion-challenger.\nTransaction NER parser - a multilingual token-classifier extracting entity types from raw descriptions.\nPayments risk and balance forecasting - quantile time-series forecasting feeding a risk/offer decision layer.\nThe enrichment suite - income / net-income, frequency detection, plus employment-loss, life-events and pay-frequency models.\nModel-quality and analytics tooling - the data-science team's own model-performance, PSI / drift and category-distribution monitoring for the models it owns.\nOur stack\nPython and SQL \nGoogle Cloud Platform \nBigQuery and modern data tooling \nPyTorch, HuggingFace and classical ML frameworks \nMLflow and Kubeflow \nFastAPI and containerized deployment \nAzure DevOps\nYou don't need experience with every tool listed above - strong production-ML fundamentals matter more than direct experience with our exact stack. Python is the exception: it's a non-negotiable (see Key Requirements).\nWhy This Role\nHigh ownership, low bureaucracy - you own models end to end and watch them drive real financial decisions for banks and fintechs.\nA modern, cloud-native ML stack with an AI-assisted development workflow.\nReal scale and real stakes - regulated financial data, enrichment and payments.\nKey Requirements\nExperience: 6-8 years building and shipping machine-learning models, including taking models to production yourself (training pipeline → served endpoint → monitoring).\nEducation: Bachelor's degree in a quantitative field (Computer Science, Statistics, Applied Mathematics, or related), a Master's or PhD is an asset, not a requirement - production-ML ability matters more than credentials here.\nNon-negotiables: production-grade Python and the ability to take a model to a live, monitored service yourself, on a solid data-science / ML foundation. A notebook-only profile won't meet the bar.\nWork authorization: must be legally authorized to work in Canada.\nBenefits\nAs part of the total rewards package, Flinks offers:\nHealth & Dental coverage as of Day 1\nFlexible Paid Time Off (FTO)\nRemote work environment with frequent in-person gatherings and activities.\nCareer development, learning opportunities and growth\nAnd more\nWe are committed to providing accommodations for persons with disabilities. If you require accommodation, we will work with you to meet your needs.\nFlinks uses artificial intelligence (AI) during the recruitment process to assist in screening, assessing, or selecting applicants.\n---------------------------------------------------------------------------------------\nÀ propos de Flinks\nFlinks est une plateforme de finance intégrée qui réunit la connectivité, l’intelligence financière et les paiements, offrant aux entreprises l’infrastructure nécessaire pour concevoir et déployer des expériences financières fluides à grande échelle.\nChef de file de la finance ouverte (Open Finance) au Canada, nous avons connu une croissance soutenue depuis 2016 pour devenir l’une des plateformes les plus fiables en Amérique du Nord en matière d’accès aux données financières, d’enrichissement des données et de mouvement de fonds. Nous collaborons avec des entreprises innovantes dans de nombreux secteurs, notamment le crédit, les technologies financières (fintech), les services bancaires, l’assurance et la gestion de patrimoine.\nAujourd’hui, notre plateforme est connectée à plus de 15 000 institutions financières à travers l’Amérique du Nord et soutient plus d’un million de connexions mensuelles. Nous offrons également à nos clients un accès à plus de 4 500 indicateurs financiers en temps réel afin de favoriser une prise de décision plus éclairée. Les entreprises s’appuient sur Flinks pour simplifier l’intégration de leurs utilisateurs, vérifier les revenus, évaluer le risque de crédit et offrir des expériences de paiement plus rapides.\nNotre mission est d’accélérer l’innovation financière et d’aider les entreprises à créer des expériences financières simples, connectées et centrées sur leurs clients. C’est là que vous entrez en jeu.\nLe poste\nNous sommes à la recherche d’un(e) Scientifique de données principal(e) (Senior Data Scientist) qui prendra en charge nos modèles d’apprentissage automatique de bout en bout : de la définition du problème et de la conception du modèle, jusqu’au pipeline d’entraînement, au déploiement en production et au suivi de la qualité du modèle une fois en service.\nIl s’agit d’un poste de science des données très pratique et fortement axé sur l’ingénierie. Vous concevrez, développerez et déploierez vos propres modèles.\nOù se situe ce rôle?\nVous êtes responsable des modèles et de leur qualité.\nL’équipe d’ingénierie des données (Data Engineering) est responsable de la plateforme de données partagée et de l’infrastructure de déploiement sur laquelle vous vous appuierez : entrepôt de données, pipelines, gouvernance, CI/CD et fiabilité opérationnelle des points de terminaison. Cela vous permet de vous concentrer sur la science des données et le cycle de vie des modèles, plutôt que sur l’exploitation de la plateforme.\nNous tenons à être transparents à ce sujet : si vous recherchez un rôle purement axé sur la recherche ou l’analyse dans des notebooks, ce poste n’est probablement pas pour vous.\nEn revanche, si l’idée de mener un modèle jusqu’à un point de terminaison en production, surveillé et utilisé pour prendre de véritables décisions financières vous motive, vous vous épanouirez chez Flinks.\nNous ne développons pas des modèles simplement pour faire du ML. Nous évaluons leur succès en fonction des résultats d’affaires qu’ils génèrent : réduction du risque, amélioration de la qualité des enrichissements, adoption par les clients, efficacité opérationnelle, croissance des revenus, etc. Faire le lien entre les améliorations apportées à vos modèles et ces résultats fait partie intégrante du rôle.\nCe que vous ferez\nPrendre en charge les modèles de ML de bout en bout : définition du problème, rédaction des documents de conception (RFC), développement, entraînement, déploiement et suivi en production.\nConcevoir les pipelines d’entraînement et préparer les modèles pour leur mise en service sur la plateforme partagée exploitée par l’équipe Data Engineering.\nAssurer la qualité des modèles, sans être responsable de la plateforme elle-même.\nSurveiller les dérives (drift), la performance et déterminer les moments appropriés pour réentraîner les modèles.\nMettre en place des processus d’évaluation rigoureux : expérimentation, validation statistique, détection de dérive, réentraînement, approches champion-challenger et promotion des modèles.\nCollaborer avec plusieurs équipes de l’organisation. Les résultats de vos modèles alimentent les couches d’attributs et d’enrichissement, les systèmes de risque liés aux paiements, les tableaux de bord et les intégrations clients.\nTravailler étroitement avec les équipes Data Engineering, Développement Backend, Produit et Assurance qualité (QA) sur les contrats de données, les déploiements et les mises en production.\nTirer parti du développement assisté par l’IA afin d’accélérer l’implémentation et l’expérimentation. Les contributions ayant le plus d’impact dans ce rôle reposent sur une excellente définition des problèmes, une solide conception de systèmes, une grande rigueur analytique et des spécifications techniques claires.\nCe sur quoi vous travaillerez\nVoici quelques-uns des systèmes de ML actuellement en production dont vous serez responsable de bout en bout :\nCatégorisation des transactions - Classificateur hiérarchique multitâche basé sur BERT, exécuté sous forme de modèles segmentés, entraîné à partir de données étiquetées et enrichi par des données synthétiques pour les catégories rares.\nDétection des annulations et de la catégorie finale- Modèle hybride combinant apprentissage automatique et règles analytiques permettant de classifier les différents types d’annulation et de les associer à leur transaction d’origine.\n Analyseur (NER) de transactions- Classificateur multilingue de type token permettant d’extraire des entités à partir de descriptions transactionnelles brutes.\nPrévision des soldes et du risque de paiement- Modèles de prévision de séries temporelles quantiles alimentant les couches décisionnelles l...","description_format":"text","description_chars":15431,"description_truncated":true,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"French","level":"Advanced (C1)","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Software & Embedded Finance","Digital Banks & Neobanks"],"lifecycle":[{"event":"open","at":"2026-09-13T17:26:38Z"}],"visa":[],"liveness":{"score":18,"band":"cold","label":"Long shot","p_open":1,"p_active":0.489,"p_room":0.36,"age_days":62,"expected_fill_days":35,"reasons":["conf:4","win:tail","crowd:"],"computed_at":"2026-11-05T05:54:30Z"},"pay":null,"html_url":"https://alion.io/job/flinks-senior-data-scientist","json_url":"https://alion.io/job/flinks-senior-data-scientist.json","meta":{"generated_at":"2026-11-06T04:37:58Z","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":7941,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-07T00:00:00Z"}},"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":58125},"rest":"https://alion.io/mcp/rest/get_company?id=58125"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fflinks-senior-data-scientist"},{"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%2Fflinks-senior-data-scientist"},{"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%2Fflinks-senior-data-scientist"},{"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/flinks-senior-data-scientist\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fflinks-senior-data-scientist"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":871406}},{"tool":"search_jobs","arguments":{"company":"flinks.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":871406},"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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