Position Description:
Develops and deploys Machine Learning (ML) enabled products and services at scale using Deep Learning (DL) methodologies related to document automation, computer vision, and natural language models. Solves business problems — Business to Consumer (B2C), Business to Business (B2B), quality operations, operations management, and automation — using Artificial Intelligence (AI) and data science techniques (Natural Language Processing (NLP), DL, ML, causal inference, predictive analytics, experimental design, and optimization). Leads a team of data scientists, collaborates closely with data engineers, system integration engineers, quality engineers, and business stakeholders to solve challenges, text analytics problems, with innovative solutions. Owns the delivery of AI-enabled applications. Provides analytic consults to the business and identifies and gathers complex data from multiple sources. Conducts experiments to test algorithms, monitor model performance, interpret findings, and present work to technical and non-technical audiences.
Primary Responsibilities:
Education and Experience:
Bachelor’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and five (5) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
Or, alternatively, Master’s degree (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and two (2) years of experience as a Director, Data Science (or closely related occupation) launching, operating, leading and implementing document processing, computer vision, and Deep Learning (DL) practices using TensorFlow, Keras, MXNET, or H2O.
Or, alternatively, PhD in (or foreign education equivalent) in Applied Mathematics, Computer Science, Engineering, Information Technology, Information Systems, Information Management, Mathematics, or a closely related field and no experience.
Skills and Knowledge:
Candidate must also possess:
[Expertise may be gained during doctoral program].
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Data Analytics and Insights
Fidelity’s working model blends the best of working offsite with maximizing time together in person to meet associate and business needs. Currently, most hybrid roles require associates to work onsite all business days of one assigned week per four-week period (beginning in September 2024, the requirement will be two full assigned weeks).
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