Senior AI and Automation Data Scientist
Full time @AI Jobs Philippines posted 4 weeks ago in Information Technology and Services Shortlist Email JobJob Detail
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Job ID 983
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Experience 3 Years
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Industry Computer Vision
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Qualifications Degree Bachelor
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Job Location Type Remote
Job Description
Hybrid – Cebu 3-5 Yrs Exp Bachelor Full-time Job Description Job Description The ideal Senior AI & Automation Scientist candidate for this role will have insurance industry experience with Natural Language Processing (NLP) and perhaps Computer Vision (CV) especially applied to data extraction problems. They will be skilled in transfer learning and possess an understanding of and capability in Deep Learning (DL). They can perform work in each of those areas by leveraging a cloud environment like Databricks on Azure with Python in a notebook and IDE environment with version control leveraging git.
They can navigate API based generative AI models like those from OpenAI. They can perform these tasks collaboratively, transparently, and seek to improve the skill of the team overall. Responsibilities Deliver production quality solutions for data extraction, classification, triaging, routing, search, etc.
Programmatically explore data, derive insights that are statistically sound, and convey findings to colleagues of varying sophistication. Label and validate datasets of various sizes, using manual methods as well as programmatic and AI driven approaches. Evaluate the performance of models and solutions-as-a-whole on practical and statistical benchmarks.
Collaborate with other scientists, engineers, product owners, and business customers to develop solutions that meet the business problem. Create, contribute to, improve, and convey technical and non-technical documentation of solutions. Qualifications Experience applying quantitative methods in a corporate environment.
Experience with Python from a functional programming paradigm, able to manage dependencies, virtual environments, and version control in git. Experience with cloud computing platforms such as Azure, AWS, or GCP. Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning.
Experience with generative algorithms (e.g., GAN, VAE, etc.) as well as foundation models (e.g., GPT-4o, SAM, Mistral). Experience developing solutions from inception through deployment. Preferred Qualifications Experience with sequential algorithms (e.g., LSTM, RNN, GRU, etc.).
Experience evaluating ethical implications of AI and considerations around controlling them. #J-18808-Ljbffr