Distinguished ML Data Scientist
Role details
Job location
Tech stack
Job description
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Investigate and recommend algorithmic/data science solutions to industrial problems
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Define and translate ambiguous concepts into well-defined questions, drive analysis of complex datasets for insights, and design data-driven experiments and incubations for emerging AI and ML technologies
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Drive the design and architecture of scalable data infrastructure and analytics platforms
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Collaborate with cross-functional teams to prototype, pilot and test ML-driven solutions
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Contribute to scientific and technical publications on AI/ML research
Requirements
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12+ years of experience in data science, advanced analytics, ML engineering, or equivalent industry experience with 4+ years in hands-on statistical modeling, machine learning, data pipelines and experimental design
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Master's degree in Computer Science, Data Science, Statistics or a related technical field; PhD degree preferred
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Deep expertise in frontier and emerging AI, ML and data science techniques and best practices, including model evaluation, training/tuning, monitoring, and governance
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Recent experience with modern AI paradigms such as: world models, foundation models, and multi-modal language models; agent-based systems and orchestration; and context retrieval and augmentation techniques
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Experience in responsible deployment practices, model drift mitigation, privacy-preserving federating learning, and AI governance best practices
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Proficiency in Python, SQL, R and machine learning libraries
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Exceptional communication and presentation skills and can articulate complex technical concepts to both technical and non-technical audiences
Desired skills and competencies
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Experience in industrial domains
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Familiarity with cloud platforms (AWS, Azure, GCP)
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Experience mentoring junior team members and leading technical programs end-to-end
What success looks like
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Compelling storyteller who can use data to influence decisions
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Ability to meaningfully influence AI roadmaps and technology direction through data-driven work
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Strong ability to translate emerging research into practical solutions
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Strong collaboration with cross-functional technical and non-technical teams