SR. Data Scientist

Responsibilities

• Design, develop, and deploy core machine learning models / algorithms for content and product recommendations.
• Support development of the AI agents with RAG and other NLP tools.
• Perform a core development of the recommendation engines.
• Perform inference and refinement of the classification engine in a healthcare niche.
• Design, develop, and deploy machine learning models, with a specialized focus on AI, NLP, recommendations and tabular data.
• Integrate scientific research findings and sports science principles into the AI engine to ensure the accuracy and effectiveness of feedback and training recommendations.
• Support building and maintaining a robust data pipelines for collecting, processing, and storing large datasets of user – system interactions
• Implement self-learning and continuous retraining mechanisms for AI models based on user performance and new scientific discoveries.
• Continuously research and evaluate new machine learning techniques and technologies to improve the platform's performance and capabilities.
• Participate in code reviews, testing, and deployment processes.

Required Skills and Qualifications

• 7+ years of experience in developing and deploying ML / AI / recom. models in a production environment.
• 7+ years of experience in software development
• Strong understanding of ML / NLP algorithms (e.g., regression, classification, clustering, recommendations, deep learning, etc.) and their applications.
• Proficiency in programming languages such as Python and experience with ML / AI / NLP and recommendation algorithms and libraries (e.g., TensorFlow, PyTorch, scikit-learn, LightGBM, LLMs, Transformers, Langchain / Langgraph, crew.ai, etc.).
• Experience with data processing and storage technologies (e.g., SQL, NoSQL databases, cloud computing platforms).
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Preferred Skills and Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
• Experience with real-time data processing and analysis.
• Experience with building and maintaining data pipelines.
• Experience with cloud computing platforms (GCP preference).
• Experience with LLMs, open-sourced and APIs
• Experience with building recommendation engines
• Experience with Healthcare projects
• Experience with building multi-agent AI systems