Job Title:

Lead Data Scientist - Assistant Vice President

Lead Data Scientist (Overall 12+ years of professional experience)

Do you want to be on the leading edge of using AI and help drive engineering and product decisions for complex financial products? AI Group at State Street has embarked on a mission to delight our business by using Generative AI  and State of the art cutting technologies to develop compelling products and services. We are looking for an experienced professional with a passion for delivering business value with AI to join our team as a Lead Data Scientist.

We are looking for a strong passionate Data Scientist with a proven track record of solving large, complex machine learning problems in a real-world software product development setting. Ideal candidates should be able to take a business or engineering problem from a PM or Engineering leader and translate it to a data science problem.

You will be delivering results through innovation and persistence with no give-up attitude.

Responsibilities:

General

• Lead data science projects or teams, aligning with business needs and delivering value.
• Drive the development and implementation of innovative algorithms and methodologies to address complex business challenges.
• Define and communicate the technical direction and strategy for the team and the project.
• Provide technical guidance and promoting best practice within the team.
• Ensure the quality of project deliverables meet the required standards.
• Tell compelling, data-driven stories visually and verbally.
• Collaborate with cross-functional teams, providing technical leadership in the development of AI-driven applications.
• Optimize for performance, scalability, and practical applicability in real-world scenarios.
• Stay up-to-date on ongoing AI development activities across the company.

Generative AI and LLM

• Develop, implement, and optimize large language models and Generative AI technologies, including training/finetuning and computation optimizations.
• Collaborate with software engineers to deploy LLM and other Generative AI models into production environments.
• Pre-train and finetune over large GPU clusters while optimizing for various trade-offs.
• Improve upon the state-of-the-art in Generative AI model architectures and training techniques.
• First-hand experience with deep reinforcement learning, fine-tuning methods (like RLHF & DPO) as well as parameter efficient techniques (like LoRA & DoRA).
• Stay up to date with the latest advancements in the field of Generative AI.

Industry research and Innovation

• Lead data science partnerships and IP improvement.
• Conduct pioneering research in Generative AI, NLP, Information Retrieval, Vision and LLMs.
• Stay abreast of the latest advancements in AI technologies.
• Mentor and guide a team of innovative individuals, fostering a culture of innovation, excellence, and continuous learning.

Management

•        Work with, leverage, and mentor other data scientists to maximize impact and throughput.

•        Live and define a culture, value and practice leadership principles.

•        Attract and retain great people; Know each individual’s capabilities and aspirations; Invest in the growth of others.

A minimum of 12 years of relevant work experience with a Bachelor's Degree or 10+ years of work experience with an Advanced degree (e.g. Masters) or 7+ years of work experience with a PhD in Computer Science, Statistics, Mathematics, Machine Learning, or related disciplines.

Core/Must Skills :

Deep expertise in data science/machine learning, deep learning, ML Engineering, MLOPs and deployment.

Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch).

Experience in deep learning frameworks (like PyTorch or TensorFlow) and distributed training tools (like DeepSpeed or Pytorch Distributed).

Excellent problem-solving skills and the ability to work independently and collaboratively.

Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing.

Strong understanding of software engineering principles and best practices.

Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories.

Industrial experience in system design, software development, and production deployment.

Top-tier performance in prestigious deep learning leaderboards or large model-related competitions.

Good to Have:

• Publications in top-tier deep learning conferences or significant contributions to prominent deep learning repositories.
• Industrial experience in system design, software development, and production deployment.
• Top-tier performance in prestigious deep learning leaderboards or large model-related competitions.
• Contributions to open-source technologies

Hybrid:

On-premise

Keywords:

Lead Data Scientist, Generative AI, Senior AI/ML Developer,Azure/AWS

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