Publié il y a 2 mois
Staff Data Scientist
@ Oscilar
Télétravail au Canada
En bref
Oscilar is hiring a Staff Data Scientist to build and implement advanced fraud detection models using machine learning and statistical techniques. The role is full-time and remote-first, with an emphasis on fraud prevention and anti-money laundering experience. The posting states competitive salary and equity, a 401k, unlimited PTO, and comprehensive health, dental and vision insurance.
Responsabilités :
- Develop advanced fraud detection models using machine learning and statistics
- Analyze large data volumes to find fraud patterns and anomalies
- Evaluate and optimize existing fraud detection models
- Collaborate with engineering, product and operations teams
- Communicate model results to technical and non-technical stakeholders
Résumé des exigences :
- 5+ years in data science or machine learning, focused on fraud or AML
- Proficiency in Python
- Experience with Apache Spark or Dask on large datasets
- Strong knowledge of machine learning and statistical techniques
- Cloud development and MLOps experience is a plus
Outils et compétences
Avantages mentionnés
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-09-01
- Première détection par notre source
- 2026-10-11
- Mise à jour du dossier source
- 2026-10-11
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Données et analytique |
| Expérience | 5 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Domicile |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Avantages mentionnés | Congés payés généreux, Régime de retraite, Actions ou participation |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Oscilar
Profil d’entreprise sauvegardé
Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.
Unify fraud defense, credit underwriting, onboarding risk, and AML compliance with Oscilar's no-code, AI-native platform
Description complète de l’entreprise
Oscilar powers real-time risk decisioning across fraud, credit, and compliance with a single, unified solution. Our no-code AI Risk Decisioning™ platform leverages agentic AI and advanced signal processing to analyze complex data, detect anomalies, and automate mission-critical decisions with speed and precision. Built by the team behind risk systems at Google, Meta, Uber, Citi, and J.P. Morgan, Oscilar combines deep technical expertise with cloud-native architecture to deliver scalability, transparency, and regulatory-grade performance.
- Abonnés LinkedIn
- 19 706
- Personnes associées sur LinkedIn
- 181
- Bureaux déclarés
- Palo Alto, CA 94301, US
- Catégories d’activité
- Operating Systems
- Cyber Security
- Security
- Autres noms enregistrés
- Oscilar
- Le profil indique une agence de recrutement
- Non
- Investissement total déclaré
- 20 000 000
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Oscilar powers real-time risk decisioning across fraud, credit, and compliance with a single, unified solution. Our no-code AI Risk Decisioning™ platform leverages agentic AI and advanced signal processing to analyze complex data, detect anomalies, and automate mission-critical decisions with speed and precision. Built by the team behind risk systems at Google, Meta, Uber, Citi, and J.P. Morgan, Oscilar combines…
| Champ | Valeur |
|---|---|
| Secteur | Technology, Information and Internet |
| Taille | 201-500 employees |
| Siège social | Palo Alto, CA |
| Type d’organisation | Privately Held |
| Fondée en | 2021 |
| Offres sur Jobsy | 3 |
| Voir la page |
Shape the future of trust in the age of AI
At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place.
Why join us:
Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.
Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.
Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.
Job Description
As a Data Scientist at Oscilar, you will be responsible for developing and implementing advanced fraud detection models to protect our customers’ business from fraudulent activities. As an early member in the ML team you will have great impact in building out our ML stack.
Responsibilities:
Develop and implement advanced fraud detection models, leveraging machine learning and statistical techniques, to identify and prevent fraudulent activities across our platform.
Collaborate with cross-functional teams, including engineering, product, and operations, to design and implement fraud detection systems and processes.
Analyze large volumes of data to identify patterns, trends, and anomalies indicative of fraudulent behavior, and develop data-driven insights to improve fraud prevention strategies.
Evaluate the performance of existing fraud detection models and systems, and continuously optimize and update them to adapt to changing fraud trends and tactics.
Stay up-to-date with the latest trends and advancements in fraud detection, data science, and machine learning, and apply this knowledge to enhance our fraud prevention capabilities.
Communicate complex data analysis and model performance results to both technical and non-technical stakeholders, driving data-driven decision-making across the organization.
Ensure data privacy and security compliance in all aspects of fraud detection and data analysis.
Requirements:
5+ years of experience in data science, machine learning, or a related field, with a focus on fraud prevention and/or anti-money laundering.
Proficiency in Python.
Fluency in cloud development (AWS, GCP, Azure, etc.) and MLOps is a plus.
Strong knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection.
Experience working with large datasets using distributed systems like Apache Spark and Dask, handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale.
Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data.
Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences.
Ability to work independently and collaboratively in a fast-paced, dynamic startup environment.
Preferred Qualifications:
Experience in the fintech, marketplaces, or financial services industry.
Knowledge of current fraud tactics and trends, as well as experience with fraud detection tools and systems.
Benefits
Compensation: Competitive salary and equity packages, including a 401k
Flexibility: Remote-first culture — work from anywhere
Health: Comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
Balance: Unlimited PTO policy
Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product
Culture: Family-Friendly environment; Regular team events and offsites
Development: Unparalleled learning and professional development opportunities
Impact: Making the internet safer by protecting online transactions
Journal
Visible seulement par vous. Conservé sur cet appareil, et dans votre compte une fois connecté.