Senior DATA

Role & responsibilities

Job Summary:

Client is seeking a visionary and highly experienced Senior Data Scientist to lead our most critical analytical initiatives. In this strategic role, you will be a thought leader, responsible for architecting innovative data science solutions that solve complex healthcare challenges and drive the company's long-term vision. You will mentor a talented team, set technical direction, and translate ambiguous business problems into tangible, high-impact machine learning systems. This position is ideal for a seasoned expert who is passionate about using data to revolutionize the healthcare industry.

Key Responsibilities:

• Lead the end-to-end design, development, and deployment of advanced machine learning models and AI-driven products that deliver significant business value.
• Act as the technical lead on complex data science projects, defining the roadmap, setting priorities, and ensuring the scientific rigor of the team's work.
• Architect and implement scalable, production-ready data science pipelines and MLOps frameworks in collaboration with engineering teams.
• Serve as a primary consultant to executive leadership and business stakeholders, translating complex data insights into strategic recommendations.
• Mentor and develop other data scientists and engineers, fostering a culture of innovation, collaboration, and continuous technical growth.
• Pioneer the adoption of new technologies, methodologies, and best practices in data science and machine learning across the organization.
• Stay at the forefront of AI/ML and healthcare technology trends to identify new opportunities for innovation and competitive advantage.
• Document methodologies, processes, and results to ensure transparency and reproducibility.
• Adhere to data privacy and security standards, including HIPAA regulations, in all data handling activities.

Required Knowledge:

• Expert-level understanding of a broad range of machine learning techniques, including deep learning (e.g., CNNs, RNNs, Transformers), NLP, reinforcement learning, and causal inference.
• Deep knowledge of MLOps best practices, including model lifecycle management, CI/CD for machine learning, model monitoring, and governance.
• Comprehensive understanding of cloud architecture and services (GCP, AWS, or Azure) for building scalable AI/ML solutions.
• Expertise in healthcare data domains, including clinical data (EHR/EMR), claims, pharmacy, and familiarity with standards like HL7/FHIR, ICD, and CPT.
• Strong theoretical foundation in statistics, mathematics, and computer science.

Required Skills:

• Mastery of Python and its data science ecosystem (e.g., scikit-learn, TensorFlow, PyTorch, MLflow).
• Exceptional SQL and data modeling skills, with the ability to work with complex, multi-source data environments.
• Proven experience in designing and building solutions on cloud platforms (e.g., Google Cloud's Vertex AI, AWS SageMaker, Azure Machine Learning).
• Proficiency with big data technologies such as BigQuery.
• Superior ability to communicate and present complex technical concepts and results to executive-level audiences.

Preferred candidate profile

Perks and benefits