CTC007689 - Data Scientist - Intermediate or senior
Secteur industriel: Information Technology
Type d'emploi: Contract
Durée: Four months
Mode de travail: Mixed
Description
Locations being consider - Mississauga, Toronto and Montreal offices.
Bilingualism is an asset but not mandatory. If we have a bilingual candidate, we’ll make sure to have a Francophone member as part of recruitment process.
Hybrid role - team members to be in office 3 days/week, like other FTEs but they are flexible. They’d like team members to at least be in office during first week (3 days), and on sprint demo days (once every 2 weeks) and as required.
Typical day to day in this role - It depends on project assignment. DS member would spend most of his/her days training, fine-tuning their models, and engaging with cross-functional team members. i.e. product managers, data engineers, ML Eng/Ops members, business stakeholders.
Top 3 skills sets and qualifications -
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NLP modelling experience, leveraging Huggingface Transformers
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Experience working on Google Cloud
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Knowledge of prompt engineering and LLMs (Large Language Models), especially RAG and PEFT.
Interview process - We’d likely have 2 interviews: 1 technical, 1 final round. All virtual.
Projects will be working on -
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Classical Speech AI
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Gen AI projects
Potential for extension or to hire full time exists but can’t confirm at this point in time.
Manager would like to see a Data Scientist Profile, not a developer profile. Someone who is able to participate in the creation of a GenAI app****. The manager would like to share with you : a simple resume is ok. Thank you very much for your collaboration, Here's the revamped job posting please : • Research, design, build, train innovative GenAI applications • Experience working on Google Cloud, leveraging best practices for cloud • Experience with Large Language Models (LLMs) and Generative AI (GenAI) technology, including but not limited to OpenAI API, ChatGPT, Gemini, Claude, Langchain, and HuggingFace Transformers. • Experience with prompt engineering, LLM APIs • Generating new use case ideas to solve business problems/improve results
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Create and maintain NLP models leveraging Huggingface Transformers
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Working on Google Cloud, leveraging best practices for cloud
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Knowledge of prompt engineering and LLMs (large language models) an asset, including PEFT and RAG
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Generating new use case ideas to solve business problems/improve results
Responsible for designing and developing predictive models and algorithms to analyze and interpret complex data sets. They use their expertise in statistics, machine learning, and data mining to identify patterns and insights in data, and communicate their findings to stakeholders. They also collaborate with other data professionals to develop data-driven solutions to business problems.