Senior Data Scientist

Salary Range: $9,333.00 - $12,576.46 monthly

SUMMARY

The Data & Analytics Unit is responsible for collecting, analyzing, and interpreting healthcare data to support decision-making across the Los Angeles County Department of Health Services (DHS).

The unit manages patient care and operational data, using analytics to identify patterns, predict outcomes, and improve service delivery.

The unit also ensures data integrity, security, and regulatory compliance.

The Senior Data Scientist manages advanced analytical projects, developing sophisticated machine learning models, and providing strategic insights to drive data-informed decision-making.

This role requires expertise in statistical modeling, data engineering, and predictive analytics, as well as the ability to mentor junior data scientists and collaborate with cross-functional teams.

The Senior Data Scientist plays a key role in designing scalable data solutions, optimizing analytical workflows, and ensuring alignment between data initiatives and organizational goals.

ESSENTIAL FUNCTIONS
1.

Advanced Data Analysis & Modeling
2.

Lead the development of predictive, prescriptive, and diagnostic models to address complex business problems and optimize decision-making processes.
3.

Apply advanced statistical methods, machine learning algorithms, and data mining techniques to analyze large and varied datasets, uncovering trends and patterns that provide actionable insights.
4.

Fine-tune and optimize models, ensuring they are scalable, efficient, and aligned with business requirements.
5.

Mentor junior data scientists and guide their model development, statistical analysis, and data science practices.
6.

Machine Learning & AI Implementation - Design, train, and optimize machine learning models for forecasting, anomaly detection, and automation.
7.

Data Engineering & Pipeline Optimization - Collaborate with engineering teams to improve data pipelines, ensure data integrity, and enhance model deployment.
8.

Insightful Reporting & Visualization
1.

Create and deliver high-quality, clear, and actionable reports and dashboards, translating complex data findings into easily understandable insights for both technical and non-technical stakeholders.
2.

Use advanced visualization tools and techniques to convey analytical results effectively to leadership and business teams.
3.

Develop and implement metrics and KPIs that measure the effectiveness of data science initiatives and model performance.
9.

Strategic Collaboration & Stakeholder Engagement
1.

Work closely with business leaders and stakeholders to define data needs and prioritize projects that align with organizational goals and objectives.
2.

Translate complex technical concepts into actionable business insights and recommendations for non-technical audiences.
3.

Collaborate with cross-functional teams, including product, engineering, and IT, to design and impl...