3 - 7 years

0 Lacs

Posted:2 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As a Data Scientist at our groundbreaking digital real estate platform in Dubai, you will play a pivotal role in transforming vast datasets into predictive models and insights that will define our competitive edge. You will have the opportunity to work on challenging problems in the PropTech space and directly influence the user experience and business strategy. Your responsibilities will include designing, training, and deploying machine learning models for the "TruValue UAE" Automated Valuation Model (AVM) to predict property values. Additionally, you will develop a personalization and recommendation engine, analyze complex datasets to identify business insights and user behavior patterns, and build predictive models for forecasting metrics such as user churn and neighborhood demand dynamics. Collaboration will be key in this role, as you will work closely with backend engineers, product managers, and business stakeholders to leverage data assets and drive personalization, market intelligence, and strategic decision-making across the platform. You will also contribute to the design and development of big data infrastructure and MLOps pipelines. To be successful in this role, you should have 3-5+ years of hands-on experience as a Data Scientist, with a proven track record of building and deploying machine learning models in a production environment. A Masters degree or PhD in a quantitative field is required, along with expert proficiency in Python and its data science ecosystem. Strong practical knowledge of various machine learning techniques, advanced SQL skills, and experience with data visualization tools are also essential. Preferred qualifications include experience in the PropTech or FinTech sectors, direct experience building Automated Valuation Models (AVMs), familiarity with cloud-based data platforms and ML services, and experience with MLOps principles and tools. Additionally, experience with time-series analysis, forecasting, and Natural Language Processing (NLP) techniques would be beneficial for this role.,

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