Data Science Supervisor

HonorVet Technologies
Los Angeles, CA, United States
3 days ago
Apply on www.dice.com
Prepare application

Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Amazon Web Services Business Logic Unit Testing Microsoft Azure Big Data Cloud Computing Software Documentation Databases Information Engineering Extract Transform Load (ETL) Data Security
+27 more
Data Visualization Data Warehousing Relational Databases Database Development R (Programming Language) Apache Hadoop Statistical Hypothesis Testing Python (Programming Language) Machine Learning NumPy Scrum Methodology Power BI SQL Databases Tableau (Software) Cloud Platform System Flask (Web Framework) Apache Spark Backend Pandas Matplotlib Scikit Learn Data Analytics Api Design Data Pipelines Docker Unsupervised Learning Databricks

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., * 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.

Requirements

  • 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.

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com
Prepare application

Good distractions

Loading talks and stories from around this role…