Data Science Supervisor: Lead ML & ETL in Cloud

Us Tech Solutions; Los Angeles (CA); On-site; USD 140,000 - 170,000; Full time

Job summary

US Tech Solutions is seeking a Data Science Supervisor in Los Angeles to lead a team of data scientists and analysts. You will direct ML model development, supervise complex projects, and ensure robust ETL pipelines and secure data practices across cloud environments.

The role emphasizes Agile leadership, technical documentation, and collaboration with engineering to deliver high-quality data products for client-centric decision making.

Qualifications

• The candidate has 6 years of experience, including 3 years supervising data science professionals.
• Expertise in ML techniques (supervised and unsupervised) and statistical analysis.
• Hands-on proficiency with Pandas, NumPy, Scikit-learn, Spark/Hadoop, Python, R, and SQL.
• Experience deploying models with Docker, Flask, or cloud platforms (AWS/Azure).
• Advanced data visualization with Tableau, Power BI, Matplotlib, or Seaborn.

Responsibilities

• Lead data science projects and supervise a team to support policy and operational decisions.
• Advise on complex database buildouts and manage backend pipelines and cloud environments (Databricks).
• Own technical and code-level documentation; co-lead system docs, API layouts, and ETL logic.
• Serve as Technical Lead for data security and Lead for QA, overseeing unit testing and code integrity.
• Engage in Agile/Scrum workflows, drive sprint planning, manage blockers, and ensure timely deliverables.

Skills

Team leadership

ML techniques

Statistical analysis

Hypothesis testing

Pandas/NumPy/Scikit-learn

Apache Spark/Hadoop

Python

R

SQL

Docker/Flask/AWS/Azure

Tableau/Power BI/Matplotlib/Seaborn

Education

Master’s degree in Data Science or related

Tools

Docker

Flask

AWS

Azure

Tableau

Power BI

Matplotlib

Seaborn

Databricks

Python

SQL

Job description

US Tech Solutions is seeking a Data Science Supervisor in Los Angeles to lead a team of data scientists and analysts. You will direct ML model development, supervise complex projects, and ensure robust ETL pipelines and secure data practices across cloud environments.

The role emphasizes Agile leadership, technical documentation, and collaboration with engineering to deliver high-quality data products for client-centric decision making.