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Job Description

We are seeking an innovative Senior Data Scientist at Devsinc to spearhead a technical team and derive actionable insights from raw data. The ideal candidate will combine expertise in data science, machine learning, and cutting-edge technologies such as DevOps, MLOps, and Retrieval-Augmented Generation (RAG). They will also integrate modern tools like LangChain, LlamaIndex, and Agentic RAG for scalable, intelligent solutions.


As the Senior Data Scientist, you will manage a multidisciplinary team of data professionals, plan and execute advanced projects, and build analytics models that align with our business objectives. Strong problem-solving skills, a passion for innovation, and experience in data engineering and MLOps pipelines are critical for success in this role.
Leadership and Team Management


- Manage a team of data scientists, machine learning engineers, big data specialists, and DevOps/MLOps experts.


- Foster collaboration across technical and business teams to deliver impactful data-driven solutions.


Data Science and Machine Learning


- Lead data mining, collection, and preparation procedures while ensuring data quality and integrity.


- Build and deploy analytic systems, predictive models, and LLM-powered solutions.


- Experiment with state-of-the-art models, including LangChain, LlamaIndex, and RAG architectures.


- Design and implement Agentic RAG workflows for dynamic, context-aware systems.


Data Engineering and MLOps


- Oversee the development and optimization of robust data pipelines.


- Implement MLOps best practices for scalable, automated machine learning deployments.


- Leverage CI/CD pipelines and containerization tools (e.g., Docker, Kubernetes) to streamline operations.


Analytics and Reporting


- Interpret complex data problems, extract insights, and visualize results through intuitive reports and dashboards.


- Collaborate with stakeholders to align data initiatives with organizational goals.


Innovation and Experimentation


- Stay updated on emerging technologies and integrate them into existing workflows.


- Experiment with LLM-based solutions and advanced generative AI methodologies.


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