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Data Scientist - JP-555
Dubai, United Arab Emirates (Full-time)
30th September 2024
About the Job
Company Description
Creo Technologies is a global technology consulting firm based in Dubai, United Arab Emirates, specializing in delivering modern data-driven solutions to enterprises. The team at Creo consists of experienced technology professionals and domain experts offering scalable solutions in advanced analytics, machine learning, data visualization, and more. With a focus on various industries, Creo is committed to delivering excellence and helping clients unlock the full potential of their data.
Role Description
This is a full-time on-site role for a Data Scientist at Creo Technologies in Dubai, United Arab Emirates. The Data Scientist will be responsible for tasks such as data analytics, statistical modeling, data visualization, and data analysis on a day-to-day basis.
Technical Qualifications & Key Experience:
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5-7 years of experience in data-science.
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Data Engineering, Cleansing, Anomaly Detection and Modeling Skills
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Proficiency in Python, R, SQL, and ML frameworks like TensorFlow, Keras, Scikit-learn.
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Familiarity with DataOps and MLOps
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Experience in Alteryx, Databricks or SAS is a plus.
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Strong communication skills to articulate technical ideas to non-tech professionals.
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Ability to lead cross-functional teams in high-stakes environments.
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Problem-solving mindset with a focus on improving patient outcomes and operational efficiency.
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Lead projects from conception to deployment, ensuring on-time delivery and model success.
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Experience on complex models including LLM and on-premise Generative AI is a plus.
Educational Background:
Bachelor's or Master’s degree in Statistics, Math, Computer Science, Data Science, or related fields.
Responsibilities:
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Analyze large volumes of structured and unstructured data.
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Develop, validate, and deploy predictive and prescriptive models to improve analysis outcome.
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Implement models for natural language processing (NLP).
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Communicate technical findings to non-technical stakeholders, ensuring models' usability and addressing ethical or regulatory concerns (e.g., HIPAA).
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Collaborate with data engineers to ensure robust data pipelines for model training and deployment.
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Monitor and maintain models post-deployment, ensuring they are regularly updated with new data to improve accuracy and performance.