Senior Data Scientist

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 a Senior Data Scientist to help us take our data innovation to the next level.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven systems across a variety of domains including NLP, recommendation engines, and generative AI.
• Lead the use of Databricks Mosaic AI for scalable model training, experimentation, and lifecycle governance.
• Leverage Azure AI services (e.g., Azure OpenAI, Cognitive Services) to operationalize and integrate intelligent capabilities into production applications.
• Utilize Azure Foundry and other cloud-native frameworks to architect robust, high-scale AI solutions.
• Translate business challenges into data science problems and deliver measurable results through applied machine learning.
• Implement and maintain enterprise-grade ML workflows with a focus on security, scalability, and performance.
• Apply a range of advanced techniques, including LLMs, prompt engineering, fine-tuning, and traditional ML methods.
• Collaborate with engineering, analytics, and product teams to deliver end-to-end AI solutions.
• Mentor junior data scientists and foster a culture of innovation, experimentation, and ethical AI use.

Required Qualifications

• 7+ years of hands-on experience in data science and ML model deployment in production environments.
• Deep expertise with Databricks Mosaic AI, including distributed training, MLOps, and governance.
• Strong experience with the Microsoft Azure ecosystem—especially Azure AI, Azure ML, Azure Foundry, and Azure Synapse.
• In-depth understanding of machine learning, LLMs, NLP, and related evaluation and integration techniques.
• Proficient in Python and libraries such as scikit-learn, PyTorch/TensorFlow, Hugging Face Transformers.
• Experience designing reproducible ML pipelines and ensuring model performance and observability.
• Familiar with MLflow, Git, Azure DevOps, and other tools used for collaboration, versioning, and model tracking.

Preferred Qualifications

• Demonstrated experience building scalable, cloud-native AI systems in a production setting.
• Knowledge of responsible AI practices, including fairness, transparency, bias mitigation, and compliance.
• Familiarity with vector databases and tools for LLM evaluation and monitoring.

Job Type: Full-time

Work Location: In person