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, data governance, 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
   
   
   
   1. Manage the development of predictive, prescriptive, and diagnostic models to address complex business problems and optimize decision-making processes.
   
   
   2. 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.
   
   
   3. Fine-tune and optimize models, ensuring they are scalable, efficient, and aligned with business requirements.
   
   
   4. Mentor junior data scientists and guide their model development, statistical analysis, and data science practices.
   
   
   
   


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


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


4. 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.
   
   
   
   


5. 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 implement data solutions that drive business impact.
   
   
   
   


6. Continuous Improvement & Research
   
   
   
   1. Stay abreast of emerging data science techniques, industry trends, and technologies to drive innovation within the team and ensure best-in-class data science practices.
   
   
   2. Research initiatives that explore new methods for data analysis, modeling, and automation.
   
   
   3. Contribute to the continuous improvement of data science workflows, tools, and methodologies within the organization.
   
   
   
   

JOB QUALIFICATIONS

The ideal candidate is an experienced data scientist with strong problem-solving expertise, and the ability to drive high-impact data initiatives. They should have deep technical proficiency in machine learning, statistical modeling, and big data processing, coupled with strong business acumen and communication skills. A passion for continuous learning and innovation is essential.

Education/Experience

• Bachelor’s or Master’s degree from an accredited institution in Data Science, Computer Science, Statistics, Mathematics, or a related field.


• 4+ years of experience in data science, advanced analytics, or a related role.


• Extensive hands-on experience in machine learning, AI, and predictive modeling.

Certificates/Licenses/Clearances

• Successful clearing through the Live Scan process with the County of Los Angeles.

Other Skills, Knowledge, and Abilities

• Advanced programming skills in Python, R, or SQL for model development and data processing.


• Expertise in cloud computing (AWS, Azure, GCP) and big data technologies.


• Strong experience with data visualization tools (Tableau, Power BI) for storytelling and reporting.


• Deep knowledge of data engineering concepts, ETL processes, and model deployment.


• Proven ability to complete data science projects from ideation to implementation.


• Excellent communication skills to present complex insights to both 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 at the forefront of industry trends.

PHYSICAL DEMANDS

Stand: Not applicable

Walk: Not applicable

Sit: Frequently

Handling / Fingering: Constantly

Reach Outward: Constantly

Reach Above Shoulder: Not applicable

Climb, Crawl, Kneel, Bend: Not applicable

Lift / Carry: Occasionally - Not applicable

Push/Pull: Occasionally - Not applicable

See: Constantly

Taste/ Smell: Not Applicable

Not Applicable = Not required for essential functions

Occasionally = (0 - 2 hrs/day)

Frequently = (2 - 5 hrs/day)

Constantly = (5+ hrs/day)

WORK ENVIRONMENT

Hybrid

EEOC STATEMENT

It is the policy of Heluna Health to provide equal employment opportunities to all employees and applicants, without regard to age (40 and over), national origin or ancestry, race, color, religion, sex, gender, sexual orientation, pregnancy or perceived pregnancy, reproductive health decision making, physical or mental disability, medical condition (including cancer or a record or history of cancer), AIDS or HIV, genetic information or characteristics, veteran status or military service.