HonorVet Technologies is a Service Disable Veteran-Owned IT staffing firm, ISO 9001 and ISO 27001 certified, working with federal agencies, state governments, and Fortune 500 enterprise clients across the US. What makes us different isn't a tagline; it's the way we work. We don't forward resumes and hope for the best. We take the time to understand where a professional like you is headed and only reach out when we genuinely believe there's a fit worth exploring.

Job Title: Data Science Supervisor
Location: Los Angeles, CA, 90012
Duration: 12+ Months
Hybrid

Job Description
We are seeking an experienced Data Science Supervisor to lead a team of data science professionals while providing hands-on technical leadership across data science, data engineering, ETL pipelines, and cloud environments.
The ideal candidate will have strong expertise in machine learning, statistical analysis, relational databases, Python, R, SQL, and data visualization. This role requires the ability to supervise technical teams, oversee complex data science projects, establish data quality and security standards, and support data-driven program, policy, and operational decision-making.
The Data Science Supervisor will collaborate with data scientists, analysts, and engineering teams to guide technical strategy, manage project deliverables, and drive Agile/Scrum activities.

Key Responsibilities

Supervise and mentor data science professionals while coordinating complex data science projects.
Provide technical leadership for database development, ETL processes, backend pipelines, and cloud environments such as Databricks.
Oversee data engineering activities, pipeline design, data warehousing, and database architecture.
Lead technical and code-level documentation while contributing to system documentation, API layouts, and ETL business logic.
Establish and oversee data security implementation, quality assurance, unit testing, and code integrity standards.
Guide the development and implementation of machine learning models using supervised and unsupervised learning techniques.
Oversee statistical analysis, hypothesis testing, regression, classification, clustering, and dimensionality reduction.
Support model deployment using Docker, Flask, and cloud platforms such as AWS and Azure.
Review technical deliverables and ensure data science solutions meet business and operational requirements.
Participate in Agile/Scrum activities, including sprint planning, daily stand-ups, technical feasibility assessments, and blocker resolution.
Coordinate deployment activities, change management, and technical deliverables across project teams.
Collaborate with stakeholders to translate business requirements into scalable technical solutions.

Required Qualifications & Technical Skills

Strong hands-on experience with Python, R, and SQL.
Proficiency in data science libraries and frameworks, including Pandas, NumPy, and Scikit-learn.
Experience with machine learning techniques, including supervised and unsupervised learning.
Strong understanding of statistical analysis and hypothesis testing.
Experience with big data technologies such as Apache Spark and Hadoop.
Hands-on experience with ETL processes, backend data pipelines, relational databases, and data warehousing.
Experience working with cloud platforms such as AWS, Azure, and Databricks.
Experience deploying machine learning models using Docker, Flask, or cloud-based platforms.
Advanced data visualization skills using Tableau, Power BI, Matplotlib, Seaborn, or similar tools.
Knowledge of API design, system documentation, data security, and quality assurance practices.
Experience with Agile/Scrum methodologies and technical project coordination.

Experience Requirements

Minimum of 6 years of relevant professional experience.
At least 3 years of experience supervising a team of data science professionals.
Demonstrated experience serving as a subject matter expert and coordinating complex data science projects.
Experience supporting program, policy, and operational decision-making through data science solutions.

Education Requirements

Master's degree from an accredited college or university in Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, Public Health, Applied Research, or a related field.
A qualifying Master's degree may substitute for up to 2 years of the minimum required professional experience.

If you are interested, feel free to reach out to me directly at

Data Science Supervisor

Key skills

About this role