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Data Scientist
2 weeks ago
About Traxccel
- At Traxccel, we're transforming the way organizations harness data to drive strategy, optimize operations, and deliver impact. Our advanced analytics and AI-driven platforms empower businesses across industries with cutting-edge insights, and we're looking for an experienced Senior Data Scientist to help us take our data innovation to the next level.
Key Responsibilities
- Design, develop, and deploy machine learning models and AI-driven solutions across domains such as NLP, recommendation systems, and generative AI.
- Drive the use of Mosaic AI (Databricks) for scalable experimentation, model training, and governance.
- Develop and operationalize models using Azure AI services (e.g., Azure OpenAI, Azure Cognitive Services) and integrate them into intelligent applications.
- Utilize Azure Foundry (or equivalent Azure data and AI frameworks) for high-scale, cloud-native AI solution design.
- Architect ML workflows for enterprise-grade applications with a focus on performance, security, and maintainability.
- Apply advanced traditional ML and LLM techniques to real-world business problems, from feature engineering to inference.
- Collaborate cross-functionally with engineering, product, and analytics teams to translate business goals into ML solutions.
- Lead and mentor junior data scientists, fostering a culture of excellence, innovation, and responsible AI.
Required Qualifications
- Minimum 7+ years of hands-on data science experience, including production-level model deployment.
- Expertise in Databricks Mosaic AI, including distributed model training, fine-tuning, and lifecycle management.
- Proficient with Microsoft Azure cloud ecosystem, especially Azure AI, Azure Machine Learning, Azure Foundry, and Azure Synapse.
- Deep understanding of ML, traditional algorithms, NLP, and LLMs (e.g., prompt tuning, evaluation, and integration).
- Strong programming skills in Python and experience with libraries such as scikit-learn, Hugging Face Transformers, PyTorch/TensorFlow.
- Familiarity with ML architecture design, including reproducibility, performance tuning, and model observability.
- Experienced with tools such as MLflow, Azure DevOps, and Git for model tracking, collaboration, and deployment.
Preferred Qualifications
- Experience designing scalable AI systems using cloud-native architectures.
- Knowledge of responsible AI practices, including fairness, transparency, and compliance in model development.
- Experience working with vector databases and LLM evaluation frameworks.