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Dataiku
AI & Machine Learning 7h ago

Technical Account Manager

Dataiku
United KingdomUnited Kingdom
Full-time
Not Disclosed
Senior-Level

Job Description

Key Skills Required

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Data ScienceMLOpsKubernetes

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Technical Account Managers are highly experienced Architects who bring both deep technical expertise and strong interpersonal skills to support a small portfolio of strategic clients (approximately 3 per TAM). They must be quick on their feet and able to put a positive spin on challenging customer situations, both in the boardroom with a client CTO and while sharing the command line with a client admin. They must be effective technically, both as communicators and doers. They must be capable of managing and maintaining a client relationship, while keeping a tight organizational watch over the technical aspects of their accounts.

How you'll make an impact

  • Collaborate with the customer and the internal account team to jointly identify short and long-term priorities and develop the associated engagement plan
  • Manage project milestones in partnership with Customer Success Managers and clients, contribute to deliverables, provide regular status updates and proactively identify and mitigate issues and risks
  • Serve as a central point for client technical information and contribute to the account strategy alongside the broader account team
  • Support the growth and effectiveness of the Field Engineering team through documentation, process improvements, and knowledge sharing
  • Act as the primary technical advisor for client teams, providing guidance and hands-on support across a range of areas, including:
    • Dataiku platform architecture and deployment
    • Platform operations and upgrades
    • Best practices for platform usage
    • Security, data management, and compute resources
    • ML-Ops, monitoring, and scaling strategies
  • Assist clients in integrating the product into their systems and troubleshoot technical challenges
  • Capture client feedback and feature requests to inform the Product and Engineering teams
  • Advise client tech leaders on complementary technologies and long-term technical strategy.
  • Explore and support advanced use cases involving Dataiku, such as edge computing, deep learning, and MLOps

What you'll need to be successful

  • 7+ years of experience in a customer-facing technical role
  • Native or bilingual proficiency in English
  • Strong communication and client relationship skills
  • Experience supporting both pre- and post-sales engagements
  • Proficiency in Linux system administration, including networking
  • Experience with identity and access management tools (e.g., LDAP, Kerberos, Active Directory, IAM)
  • Hands-on experience with cloud platforms (AWS, Azure, GCP)
  • Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting and tuning
  • Familiarity with the Hadoop and/or Spark ecosystems

How you'll stand out

  • Experience with Python
  • Data-Science knowledge
  • Basic knowledge of Java
  • Familiarity with ML-Ops practices and tools

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Dataiku is a massive, highly disruptive enterprise AI and machine learning platform fundamentally designed to democratize data science and bring "Everyday AI" to global organizations. Founded in 2013 by Florian Douetteau, Clément Stenac, Marc Batty, and Thomas Cabrol in Paris (and now headquartered in New York City), the company operates as the ultimate collaborative digital operating system for data teams. Under the hood, Dataiku seamlessly bridges the gap between advanced data scientists, data engineers, and business analysts—providing a unified, end-to-end environment for data preparation, predictive modeling, MLOps, and cutting-edge Generative AI integration. Their primary target audience spans massive Fortune 500 enterprises (including industry heavyweights like Unilever, GE, and BNP Paribas) who desperately need to break down data silos, scale their AI initiatives, and transition from clunky legacy analytics to fully automated, predictive data pipelines. What sets Dataiku apart in the fiercely competitive AI landscape is its uncompromising commitment to visual, low-code/no-code collaboration; completely empowering non-technical domain experts to build robust machine learning models while still offering deep, code-first flexibility for elite engineering teams.

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