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Tier-1 brand, mid-level generalist title, metro location, and broad ML/LLM skills drive high competition.
Advanced ML/LLM skills are transferable, though financial domain context increases domain specificity to medium.
Requires Master's degree, explicit 2+ years, and specific ML/LLM tech skills, indicating medium strictness.
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Develop and operationalize AI/ML solutions including predictive modeling, NLP, LLMs, and deep learning to solve business problems within Fidelity Workplace Investing.
Lead end-to-end predictive modeling lifecycle: data analysis, feature engineering, model building, validation, scalability, and decision strategy formulation.
Collaborate with diverse business stakeholders to identify needs and deliver impactful AI/ML applications, including agentic AI and autonomous task automation.
Master’s Degree in Engineering, Computer Science, Mathematics, Computational Statistics, Operations Research, Machine Learning or related technical fields.
At least 2 years of prior work experience as a data scientist.
Technical proficiency in Python, SQL, cloud platforms (AWS or Azure), AI/ML algorithms, deep learning, NLP, LLM fine-tuning, and predictive modeling lifecycle.
Experience or familiarity with agentic AI tools (e.g., LangChain, AutoGen), and AI-centric frameworks like PyTorch; exposure to vector databases and transformer architectures is a plus.
Experienced in deploying full-cycle AI/ML projects with ability to operationalize models at scale and integrate with business strategies.
Strong technical skills in advanced AI technologies (NLP, LLMs, agentic AI) combined with cloud computing expertise.
Able to translate complex analytics into actionable business insights and communicate effectively across technical and business audiences.