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Location
In office (Tempe)
Seniority
Middle · 5+ years exp

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 9, 2026.

Overview
Company
Impact
Profile match
Leading the Way inInnovation and Excellence. With a strong foundation in Malaysia, we are proud to have a dedicated team of over 1,000 employees working around the clock to deliver exceptional service. By combining modern technology with expert knowledge, we help drive your business forward.

Your Daily Mission

 

Centauri Health Solutions is seeking a visionary and highly experienced 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.

 

Who You Are

A Master’s degree or PhD in a quantitative field such as Computer Science, Data Science, Statistics, Physics, or a related discipline.

5-8+ years of hands-on experience in data science, with a clear progression of responsibilities and impact.

A robust portfolio of successfully launched machine learning projects that have delivered significant business value in a production environment.

Demonstrated experience in a technical leadership or mentorship role.

Experience in the healthcare or life sciences industry is strongly preferred.

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.

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.

 

The Reality of the Role

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.

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