Data Science-Manager

Specifically, you will be expected to:

• Lead the application of rigorous data science within your workstream, managing and supervising junior resources through the entire data science development and deployment lifecycle.
• Collaborate with subject matter experts to obtain a deep understanding of the underlying business problem, and to define and refine the corresponding technical solution
• Co-lead the planning and strategy of current and prospective projects with subject matter experts, and effectively prioritize goals and objectives
• Stay up to date with the latest trends, techniques, and advancements in data science and identify opportunities for their application
• Actively mentor Data Scientists and Junior Data Scientists on good software practices
• Architect ML pipelines and actively contribute high-quality, production-ready code (readable, well-tested, with well-designed APIs)

Qualifications

Required:

• 8+ years of relevant industry experience leading the design, development, and deployment of machine learning models
• Experience being the technical lead for multiple project teams simultaneously
• Expert understanding of the state of the art of two or more fields in artificial intelligence; NLP and generative AI, probabilistic graphical models, time-series analysis, weak supervised learning, etc
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• Previous experience mentoring, training, and developing junior members of the team; experience in employee performance reviews
• Expert understanding of Python and other common languages
• Deep understanding of machine learning model development life cycles
• Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain
• Extensive experience with at least one cloud-based ecosystem (Azure, GCP, AWS)
• Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.)
• Demonstrated ability to write high-quality, production-ready code (readable, well-tested, well-documented, with well-designed APIs)
• Demonstrated ability to develop novel machine learning methods that go beyond putting together existing open-source code, and to apply problem-solving skills to complex issues
• Solid understanding of Docker, Jenkins, Kubernetes, and other DevOps tools
• Excellent written and verbal communication skills
• Ability to travel as needed (<25%)

Preferred:

• PhD in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
• 10+ years of industry experience leading the design, development, and deployment of machine learning models
• Prior scientific publication history. Outstanding academic track record as evidenced by top tier publications.
• Strong competency for additional coding languages (R, etc.)
• Strong project management and delivery experience, including budget oversight and staffing of project teams including time management
• Extensive experience with Microsoft Azure, including certification in machine learning
• Experience with machine learning pipelines (Azure ML)
• Experience with ML Ops and related governance processes, particularly within a regulated industry
• Strong presentation skills using Microsoft Office suite (Visio, PowerPoint, etc.)
• Understanding of the capital markets, and the role public accounting firms play