Lead Data Scientist (ML/GenAI)

We are looking for a Lead Data Scientist to drive the development, implementation, and optimization of AI and machine learning models, with a focus on generative AI, large language models (LLMs), and predictive analytics. This role will play a strategic leadership role, guiding data-driven decision-making and ensuring that AI solutions are effectively integrated into business processes.

As a technical leader, you will architect AI/ML solutions, mentor junior data scientists, and collaborate with business leaders, engineers, and product teams to turn raw data into meaningful insights. The ideal candidate will have extensive hands-on experience in AI model development, data engineering, and statistical analysis, as well as the ability to translate complex technical concepts into actionable business strategies.

• Lead the development and deployment of AI/ML models, ensuring alignment with business objectives.

• Oversee data science strategy, providing thought leadership on best practices, emerging trends, and innovation in AI/ML.

• Collaborate with cross-functional teams, including product managers, engineers, and business leaders, to identify AI-driven opportunities.

• Architect scalable AI pipelines, incorporating state-of-the-art techniques such as retrieval-augmented generation (RAG), LLM optimization, and predictive modeling.

• Mentor and guide junior data scientists, fostering a culture of continuous learning and technical excellence.

• Implement MLOps best practices, ensuring robust model monitoring, retraining, and lifecycle management.

• Communicate AI-driven insights effectively, presenting findings to stakeholders in both technical and non-technical terms.

• 5+ years of experience in data science, AI, or machine learning, with a proven track record of leading AI projects.

• Proficiency in machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, and XGBoost.

• Deep understanding of LLMs and generative AI techniques, including RAG, vector databases, and model fine-tuning.

• Experience in AI/ML deployment on cloud platforms (AWS, Azure, or GCP).

• Strong programming skills in Python, SQL, and data engineering tools.

• Expertise in data pipeline development, feature engineering, and large-scale data processing.

• Proficiency in MLOps principles, including orchestration tools, CI/CD for ML, and model monitoring.

• Proven ability to lead and mentor teams, fostering collaboration and technical growth.

• Familiarity with LangChain, LlamaIndex, Haystack, Azure AI Studio, and retrieval-augmented generation pipelines.

• Experience working with big data frameworks (Hadoop, Spark) for large-scale data handling.

• Background in financial services, revenue cycle management, or collections is a plus but not required.

• Master's or PhD in Computer Science, Machine Learning, AI, or a related field, or equivalent industry experience.

• Proven experience leading AI teams or large-scale AI initiatives.