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3 дня назад

Principal Data Scientist (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Singapore
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Principal Data Scientist (AI): Leading the design and delivery of scalable Python-based machine learning and AI solutions from discovery through production, with an accent on model evaluation, MLOps, responsible AI, and stakeholder leadership. Focus on architecting production-grade systems, evaluating generative AI and multimodal solutions, and embedding governance, security, privacy, and regulatory controls.

Location: Singapore, Singapore; hybrid work mode.

Company

hirify.global is hiring a principal-level data science and AI leader for its Data, BI & Analytics area.

What you will do

  • Set technical direction for complex data science and AI initiatives, aligning solutions with business strategy, user needs, risk appetite, and measurable outcomes.
  • Lead end-to-end delivery from opportunity identification and data assessment through experimentation, deployment, adoption, monitoring, and continuous improvement.
  • Architect and build scalable, maintainable Python-based ML and AI solutions across structured and unstructured data.
  • Define evaluation frameworks, baselines, acceptance criteria, and measures for performance, reliability, fairness, drift, operational readiness, and business impact.
  • Advise senior stakeholders and clients, lead workshops and architecture reviews, present recommendations to C-level audiences, and shape propositions, proposals, and pre-sales activities.
  • Lead technical workstreams, mentor data scientists and engineers, and collaborate with data engineering, MLOps, platform, product, and application engineering teams on reusable capabilities.

Requirements

  • Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or Engineering, supported by an undergraduate Computer Science degree or prior professional software engineering experience.
  • 9–12 years of extensive hands-on experience delivering data science, machine learning, or AI solutions, with technical leadership and measurable enterprise or client impact.
  • Deep expertise in applied machine learning, statistics, experimental design, and model evaluation.
  • Advanced proficiency in Python and SQL, including production-quality, testable, maintainable code and technical architecture.
  • Experience across the full ML lifecycle: data preparation, feature engineering, model development, validation, deployment, monitoring, and retraining, with MLOps principles.
  • Ability to lead complex cross-functional initiatives, mentor practitioners, raise engineering standards, and influence decisions without formal authority.
  • Exceptional written and verbal communication skills, including presenting technical topics, recommendations, and business value to clients, senior leaders, and non-technical audiences.

Nice to have

  • Experience designing and evaluating generative AI solutions involving large language models, retrieval-augmented generation, agentic workflows, document intelligence, OCR, multimodal models, or vision-language models.
  • Experience with Databricks, experiment tracking, model registries, and automated ML delivery pipelines.
  • Knowledge of APIs, version control, automated testing, CI/CD, containerization, cloud deployment, observability, and production support.
  • Experience in a regulated industry and practical knowledge of data protection, security, explainability, model risk management, and responsible AI controls.
  • Experience in consulting, client delivery, solution discovery, proposal development, or pre-sales.

Culture & Benefits

  • Regular employment with a hybrid work mode in Singapore.
  • Work includes responsible AI, security, privacy, model governance, and regulatory requirements throughout the solution lifecycle.
  • hirify.global emphasizes diverse, inclusive, and equitable teams and encourages applications from candidates who may not match every qualification.

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