Data Scientist - Remote

March 21

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In All Media

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In All Media is a global community-driven service organization specializing in agile development services. The company focuses on developing digital solutions through a collaborative approach that leverages swarming intelligence and team dynamics. They are dedicated to aligning industry needs with the interests of their technical community members, who possess extensive experience in various domains such as UX/UI design, quality engineering, cloud computing, big data, Salesforce, and more. In All Media emphasizes a secure development environment and a strong collaborative spirit, striving for innovation and excellence in software production. Their model relies on pre-established teams with substantial past experience working together, ensuring efficient and effective delivery of customized development solutions.

User Experience • UI Engineering & Visual Design • Mobile Experience and engineering • Consumer Experience • Enterprise Consumerization

1001 - 5000 employees

☁️ SaaS

🏢 Enterprise

🤝 B2B

📋 Description

• Develop and implement end-to-end synaptic-based models prepared for production deployment. • Conduct comprehensive data exploration and preprocessing to ensure data quality, integrity, and readiness for analysis. • Design and optimize embeddings, retrieval models, and evaluation metrics to enhance model performance. • Architect, develop, and deploy machine learning models from the ground up, ensuring seamless integration with existing infrastructures. • Perform Java code reviews and write optimized SQL queries for efficient data processing.

🎯 Requirements

• Python – Advanced proficiency in developing and optimizing machine learning models. • SQL – Strong experience in querying and managing large datasets. • Java – Proficiency in reviewing and optimizing code for machine learning applications. • Deep Learning & Large Language Models (LLMs) – Expertise in designing and implementing deep learning solutions. • Machine Learning & Model Deployment – Extensive experience in end-to-end ML pipeline development and deployment. • Data Pipeline Engineering – Proficiency in designing and maintaining scalable data pipelines. • Version Control Systems (Git) – Strong command of code versioning best practices.