Scientifique de données principal(e) senior / Senior Staff Data Scientist

Posted One Month Ago
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Montréal, QC, CAN
In-Office
Senior level
Software
Zendesk is a service-first CRM company that builds software designed to improve customer relationships.
The Role
Develop machine learning and AI security solutions to detect anomalous activity, abuse, fraud, and security risks. Analyze large behavioral datasets, build and improve detection models, evaluate Zendesk AI features, and guide production implementation. Collaborate with security, engineering, research, and product teams; mentor colleagues; monitor model performance; and translate technical findings into actionable prevention strategies.
Summary Generated by Built In
Job Description

À propos du poste

À titre de scientifique de données principal(e) chez Zendesk, vous joindrez l’équipe responsable de la sécurité de l’IA. Vous serez chargé(e) de concevoir et de développer des approches d’apprentissage automatique et d’intelligence artificielle qui nous aideront à comprendre et à détecter les activités anormales ainsi que les risques liés à la sécurité de l’IA.


Dans le cadre de ce poste, vous collaborerez avec des ingénieur(e)s en sécurité, des ingénieur(e)s logiciels, des chercheurs et chercheuses en apprentissage automatique ainsi que des équipes de produits. Vous contribuerez à fournir des informations exploitables et des modèles pouvant être utilisés pour protéger les clients de Zendesk et prévenir les abus de nos produits.


Principales responsabilités
  • Exploiter et développer notre plateforme d’évaluation de la sécurité de l’IA afin de tester les fonctionnalités d’IA de Zendesk.
  • Analyser de grands volumes de données comportementales et de données d’interaction des utilisateurs et utilisatrices afin de détecter les tendances associées aux abus, et automatiser les méthodes d’analyse.
  • Développer des modèles et des techniques de détection viables à partir de données hors ligne, afin d’éclairer et de guider leur mise en œuvre par les équipes d’ingénierie en production.
  • Améliorer la précision des systèmes existants de détection des pourriels, tout en réduisant au minimum les faux positifs.
  • Collaborer avec des équipes interfonctionnelles afin de mettre en œuvre des stratégies de prévention fondées sur les informations tirées des données.
  • Se tenir au courant des dernières tendances en matière de sécurité de l’IA.
  • Encadrer les membres de l’équipe et assurer un leadership technique dans le cadre de projets.
  • Collaborer avec les équipes de sécurité et de produits relativement aux nouveaux enjeux liés aux données, et leur fournir une expertise en science des données.

Qualifications requises
  • Diplôme d’études supérieures en informatique, en statistique, en mathématiques appliquées ou dans un domaine quantitatif connexe, ou expérience pratique équivalente.
  • Au moins cinq ans d’expérience dans l’application de l’apprentissage automatique ou de l’intelligence artificielle à des domaines tels que la détection des fraudes, la détection des anomalies ou la sécurité.
  • Solides compétences en programmation SQL et Python, ainsi qu’une bonne maîtrise des cadres de traitement des données.
  • Maîtrise de la programmation assistée par l’IA — par exemple, Claude Code et Cursor AI — et d’autres outils d’IA permettant d’accélérer les flux de travail.
  • Expérience de diverses techniques statistiques, d’apprentissage automatique, d’exploration de données et d’analyse de séries chronologiques, notamment une solide compréhension des particularités des techniques de détection des anomalies et de leurs propriétés statistiques, comme la gestion des ensembles de données déséquilibrés et des données éparses.
  • Expérience de l’utilisation de grands ensembles de données et d’environnements informatiques distribués, comme Spark et Snowflake.
  • Excellentes aptitudes en communication et capacité à expliquer des concepts techniques complexes à des personnes qui ne sont pas spécialistes du domaine.

Qualifications souhaitées
  • Expérience démontrée dans la mise en œuvre, à grande échelle, de systèmes de détection des anomalies ou d’évaluation de la sécurité de l’IA.
  • Expérience avec des outils de simulation d’attaques et d’évaluation de la robustesse des systèmes d’IA (« AI Red Teaming »).
  • Connaissance des concepts de cybersécurité et des vecteurs d’attaque courants.
  • Expérience de la surveillance et de la maintenance de modèles d’apprentissage automatique en production, ainsi que de la compréhension de l’incidence sur les clients des mécanismes de protection et des modèles de filtrage ou de pare-feu.

English Version
About the Position

As a Staff Data Scientist at Zendesk, you will be joining the AI Security team and be responsible for envisioning and developing machine learning and AI approaches that help us understand and identify anomalous activity and AI Security risks. The role involves collaboration with Security Engineers, Software Engineers, ML researchers, and product teams to share actionable insights and models that can be used to keep Zendesk's customers safe and prevent product abuse.


Key Responsibilities
  • Run and develop our AI Security evaluation platform to test Zendesk AI features.
  • Analyze large volumes of behavioral and user interaction data to identify patterns of abuse, and automatize methodology.
  • Develop viable detection models and techniques using offline data that can inform and guide engineering implementation in production
  • Improve detection accuracy for existing spam detection projects while minimizing false positives
  • Collaborate with cross-functional teams to implement prevention strategies based on data insights
  • Know the latest trends in AI Security
  • Mentor and provide technical leadership on projects
  • Collaborate with our Security and Product teams on emerging data challenges and provide data science expertise
Required Qualifications
  • Advanced degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field, or equivalent practical experience
  • 5+ years of experience applying ML/AI in areas such as fraud detection, anomaly detection, or security
  • Strong programming skills in SQL and Python, with proficiency in data processing frameworks
  • Fluency in AI-assisted programming (e.g., Claude Code, Cursor AI) and other AI tools to accelerate workflows.
  • Experience with a variety of Statistical, ML, data mining, and time series techniques, including strong experience with the specificities of anomaly detection techniques and their statistical properties (e.g., knowing how to deal with unbalanced datasets, sparsity)
  • Experience working with large datasets and distributed computing environments (e.g., Spark, Snowflake)
  • Strong communication skills with ability to translate complex technical concepts to non-technical collaborators
Preferred Qualifications
  • Proven track record implementing anomaly detection or AI Security evaluation systems at scale.
  • Experience with AI Red Teaming tools.
  • Knowledge of cybersecurity concepts and common attack vectors.
  • Experience with ML model monitoring, maintenance in production, and customer impact of guardrails and firewall models. 

The intelligent heart of customer experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [email protected] with your specific accommodation request.

Skills Required

  • Advanced degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field, or equivalent practical experience
  • 5+ years of experience applying machine learning or artificial intelligence in fraud detection, anomaly detection, security, or related areas
  • Strong programming skills in SQL and Python
  • Proficiency with data processing frameworks
  • Fluency in AI-assisted programming tools such as Claude Code or Cursor AI
  • Experience with statistical, machine learning, data mining, and time series techniques, including anomaly detection, unbalanced datasets, and sparsity
  • Experience working with large datasets and distributed computing environments such as Spark or Snowflake
  • Strong communication skills and ability to explain technical concepts to non-technical collaborators
  • Track record implementing anomaly detection or AI security evaluation systems at scale
  • Experience with AI red teaming tools
  • Knowledge of cybersecurity concepts and common attack vectors
  • Experience with machine learning model monitoring and production maintenance
  • Experience with customer impact of guardrails and firewall models

Zendesk Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zendesk and has not been reviewed or approved by Zendesk.

  • Fair & Transparent Compensation — The company states a commitment to publishing base pay ranges and advancing pay equity, helping employees gauge fairness. Public messaging on pay equity and transparency signals structured, consistent compensation practices.
  • Leave & Time Off Breadth — Time away programs include flexible PTO, dedicated well‑being days, emergency time off, and pregnancy loss leave. Parental leave is described as generous, and travel support exists for reproductive care where access is restricted.
  • Healthcare Strength — Benefits language highlights comprehensive medical, dental/vision, mental health access, and an employee assistance program. These offerings are positioned as part of holistic wellbeing support across regions.

Zendesk Insights

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The Company
HQ: San Francisco, CA
6,277 Employees
Year Founded: 2007

What We Do

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love. We advocate for digital first customer experiences— and we stick with it in our workplace. Over 5,000 employees worldwide are collaborating from kitchen tables, home offices, co-working spaces, and Zendesk workspaces to make one team.

Why Work With Us

We know one desk doesn’t fit all. At Zendesk, we prioritize remote work because we believe great work happens anywhere. Digital first is more than where we work though. We give our employees flexibility and choice in both where and how they work while also trusting them to be a team player.

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