[Remote] Data Scientist
Note: The job is a remote job and is open to candidates in USA. Magnify is partnering with a leading organization to identify a Data Scientist for its data and technology organization. The role focuses on developing, deploying, and managing production machine learning models, AI solutions, and data products, including LLM and RAG applications. The position involves collaborating with product, engineering, and business stakeholders across the full machine learning lifecycle.
Responsibilities
- Develop and deploy machine learning models and AI-powered data products
- Turn business challenges into scalable data science and modeling solutions
- Analyze large datasets to uncover insights and improve products and business processes
- Build data collection and automation tools
- Prepare datasets and perform feature engineering for ML applications
- Apply techniques such as classification, regression, NLP, clustering, and optimization
- Evaluate model performance and continuously improve solutions
- Develop and support AI applications involving LLMs and Retrieval-Augmented Generation (RAG)
- Help integrate models into applications through APIs, pipelines, and other services
- Work with engineering teams to move models from development into production
- Deploy and manage solutions using cloud technologies such as Azure, AWS, Azure Machine Learning, or SageMaker
- Participate in model testing, validation, documentation, and lifecycle management
- Contribute to technical architecture and solution design discussions
- Develop A/B testing approaches to measure model and product performance
- Follow established SDLC, version control, testing, and release practices
- Present technical findings and explain model results to both technical and business audiences
- Stay current with emerging AI and machine learning technologies
Skills
- 2–5+ years of experience in Data Science, Machine Learning, AI, or a related field
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline
- Strong experience with Python and SQL
- Hands-on experience developing and deploying ML models in production
- Strong understanding of machine learning and statistical modeling
- Experience with techniques such as:
- Classification and regression
- Decision trees
- Neural networks
- Clustering
- Natural Language Processing (NLP)
- Experience with cloud environments such as AWS or Azure
- Familiarity with Azure Machine Learning, AWS SageMaker, Azure OpenAI, AWS Bedrock, or similar platforms
- Experience working with APIs, data pipelines, and production integrations
- Understanding of software development lifecycle practices
- Strong communication and problem-solving skills
- Ability to collaborate effectively with technical and non-technical stakeholders
- Experience with LLMs and/or RAG is highly desirable
Benefits
- Remote or Hybrid
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