Data Scientist Supervisor
About The Position
The Data Scientist Supervisor leads a team within the Los Angeles County Department of Health Services (DHS) Data & Analytics Unit. The unit collects, analyzes, and interprets healthcare data to support decision-making, improve service delivery, and ensure data integrity, security, and regulatory compliance. The supervisor oversees advanced analytical projects, machine learning initiatives, and data-driven strategies, including the development and implementation of predictive models and optimization of data workflows. The role provides technical leadership, mentors team members, and fosters collaboration, innovation, and efficiency in data science operations. The position applies advanced statistical methods, machine learning algorithms, and data mining techniques to large and varied datasets; develops, fine-tunes, and deploys scalable analytical models; and translates complex findings into actionable recommendations for technical and non-technical stakeholders. It collaborates with engineering, IT, business teams, and organizational leaders to integrate data science solutions into operational processes and continuously improve methods, tools, and workflows.
Requirements
- Master’s degree from an accredited institution in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- At least 6 years of experience in data science, including at least 2 years in a leadership role.
- Extensive hands-on experience in machine learning, AI, and predictive modeling.
- Proven experience leading and mentoring data science teams.
- Advanced programming skills in Python, R, and SQL for model development and data processing.
- Expertise in cloud computing (AWS, Azure, or GCP) and big data technologies.
- Strong experience with data visualization tools such as Tableau and Power BI.
- Deep knowledge of data engineering concepts, ETL processes, and model deployment.
- Proven ability to lead data science projects from ideation through implementation.
- Excellent communication skills, including presenting complex insights to technical and non-technical audiences.
- Experience mentoring junior data scientists and fostering a data-driven culture.
- Strong understanding of agile methodologies and project management principles.
- Commitment to innovation and staying current with industry trends.
- Successful clearing through the County of Los Angeles Live Scan process.
Responsibilities
- Lead, coach, and mentor data scientists, fostering continuous learning and professional growth.
- Manage and oversee development of machine learning models and analytical solutions that meet business needs.
- Apply advanced statistical methods, machine learning algorithms, and data mining techniques to analyze large and varied datasets and uncover actionable insights.
- Fine-tune and optimize models to ensure they are scalable, efficient, and aligned with business requirements.
- Guide junior data scientists in model development, statistical analysis, and data science practices.
- Collaborate with engineering teams to ensure data pipelines are scalable, efficient, and accurate.
- Establish and enforce best practices for data science methodologies, model validation, and documentation.
- Lead development of predictive, prescriptive, and diagnostic models for complex problems and decision-making.
- Design, train, and optimize machine learning models for forecasting, anomaly detection, and automation.
- Create and deliver clear, actionable reports and dashboards for technical and non-technical stakeholders.
- Use visualization tools and techniques to communicate analytical results to leadership and business teams.
- Develop and implement metrics and KPIs to measure data science initiatives and model performance.
- Work with business leaders and stakeholders to define data-driven strategies and deliver actionable insights.
- Translate technical concepts into business insights and recommendations for non-technical audiences.
- Partner with IT, engineering, and business teams to integrate data science solutions into operational processes.
- Keep abreast of data science techniques, industry trends, and technologies to drive innovation and maintain strong practices.
- Lead research into new methods for data analysis, modeling, and automation.
- Continuously improve data science workflows, techniques, methodologies, tools, and technologies.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
