Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Creates alternative model approaches to assess complex model design and advance future capabilities. Mentors and develops junior data scientists and analysts.

Qualifications:

• PhD or Master in a relevant discipline such as Computer Science, Cognitive Science, Mathematics, Statistics, Physics, Electrical & Computer Engineering.
• Strong expertise in various AI/ML concepts and paradigm. Strong expertise in at least one or more of the following areas: Large Language Models, Natural Language Processing, Reinforcement Learning, Knowledge Graph, Time-Series Analysis, or Generative AI.
• Experience with machine learning development lifecycle and AI/ML methods such as Transformers, Diffusion Models, SHAP, LLM and GenAI etc.
• Strong software engineering capabilities and hands-on experience with various machine learning and deep learning frameworks including numpy, scikit-learn, keras, PyTorch and Tensorflow
• A strong understanding of the real-world advantages and drawbacks of various algorithms and the ability to measure success.
• Ability to write clean, understandable code that follows leading industry standards and practices and is well-documented, and to build easily reproducible models

• Leads the execution of large scale, more complex analytics projects. Applies significant quality control and risk assessment of the model, methodologies, outputs, and processes for major data science projects.
• Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Creates alternative model approaches to assess complex model design and advance future capabilities. Mentors and develops junior data scientists and analysts.
• Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps.
• Engages with senior leadership to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach.
• Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.
• Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders.
• Participates in special projects and performs other duties as assigned.

Qualifications:

• PhD or Master in a relevant discipline such as Computer Science, Cognitive Science, Mathematics, Statistics, Physics, Electrical & Computer Engineering.
• Strong expertise in various AI/ML concepts and paradigm. Strong expertise in at least one or more of the following areas: Large Language Models, Natural Language Processing, Reinforcement Learning, Knowledge Graph, Time-Series Analysis, or Generative AI.
• Experience with machine learning development lifecycle and AI/ML methods such as Transformers, Diffusion Models, SHAP, LLM and GenAI etc.
• Strong software engineering capabilities and hands-on experience with various machine learning and deep learning frameworks including numpy, scikit-learn, keras, PyTorch and Tensorflow
• A strong understanding of the real-world advantages and drawbacks of various algorithms and the ability to measure success.
• Ability to write clean, understandable code that follows leading industry standards and practices and is well-documented, and to build easily reproducible models.