Job Title: Data Scientist
Location: Los Angeles, CA
Duration: 9 Months + Extension
Bill Rate: $68/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Job Description:

• We are seeking an experienced Data Science Supervisor to lead a team of data scientists and analysts in delivering advanced data science solutions. The ideal candidate will have strong expertise in machine learning, statistical analysis, data engineering, ETL pipelines, relational databases, and cloud platforms. This role requires both technical leadership and team management skills, with the ability to oversee complex projects and support data-driven business and operational decisions.

Key Responsibilities:

• Lead, mentor, and supervise data scientists and analysts while ensuring quality and timely project delivery.
• Oversee relational databases, database architecture, ETL processes, backend pipelines, and cloud environments such as Databricks.
• Develop and implement machine learning models using supervised and unsupervised learning techniques.
• Perform statistical analysis, regression, classification, clustering, dimensionality reduction, and hypothesis testing.
• Manage data processing and analytics using Python, R, SQL, Pandas, NumPy, and Scikit-learn.
• Work with big data technologies such as Apache Spark and Hadoop.
• Support machine learning model deployment using Docker, Flask, AWS, and Azure.
• Develop data visualizations, dashboards, and reports using Tableau, Power BI, Matplotlib, and Seaborn.
• Oversee technical documentation, API design documentation, ETL business logic, data security, and quality assurance.
• Establish code review practices, unit testing, and code quality standards.
• Lead Agile/Scrum activities, including sprint planning, daily stand-ups, task assignments, and blocker resolution.
• Collaborate with engineering teams and stakeholders to ensure successful deployment and support data-driven decision-making.

Required Qualifications:

• Minimum 6 years of relevant professional experience.
• At least 3 years of experience supervising data science professionals.
• Strong experience managing complex data science projects and technical teams.
• Hands-on expertise in Python, R, SQL, and machine learning.
• Experience with relational databases, ETL pipelines, data engineering, and data warehousing.
• Knowledge of cloud platforms, preferably AWS, Azure, or Databricks.