Data Science Lead: ML, ETL, Cloud & Analytics

Robotics Technologies; Los Angeles (CA); On-site; USD 77,000 - 110,000; Full time

Job summary

Robotics Technologies LLC in Los Angeles seeks an experienced Data Science Supervisor to lead a team of data scientists and analysts in delivering advanced data science solutions. The role requires expertise in ML, statistical analysis, ETL pipelines, databases, and cloud platforms, with responsibility for technical leadership and project oversight to support data-driven decisions.

Candidates should have hands-on Python/R/SQL, experience with Databricks, Spark, Hadoop and deployment via Docker,

Qualifications

• Minimum 6 years of relevant professional experience.
• At least 3 years of experience supervising data science professionals.
• Hands-on experience leading data science projects and technical teams.
• Strong programming in Python, R, SQL and ML.
• Experience with relational databases, ETL, data warehousing, and cloud platforms.

Responsibilities

• Lead, mentor, and supervise data scientists and analysts to ensure quality and timely delivery.
• Oversee databases, ETL processes, backend pipelines, and cloud environments such as Databricks.
• Develop and implement ML models using supervised and unsupervised techniques.
• Perform statistical analyses, regression, classification, clustering, and hypothesis testing.
• Manage data processing using Python, R, SQL, Pandas, NumPy, and Scikit-learn.
• Work with big data technologies like Spark and Hadoop.
• Support model deployment using Docker, Flask, AWS, and Azure.
• Develop data visualizations and dashboards using Tableau and Power BI.
• Lead Agile/Scrum activities and collaborate with engineering teams.

Skills

Python

R

SQL

Machine learning

Leadership

Project management

Tools

Databricks

Tableau

Power BI

Docker

Flask

AWS

Azure

Hadoop

Apache Spark

Job description

Robotics Technologies LLC in Los Angeles seeks an experienced Data Science Supervisor to lead a team of data scientists and analysts in delivering advanced data science solutions. The role requires expertise in ML, statistical analysis, ETL pipelines, databases, and cloud platforms, with responsibility for technical leadership and project oversight to support data-driven decisions.

Candidates should have hands-on Python/R/SQL, experience with Databricks, Spark, Hadoop and deployment via Docker,