Data Scientist - Python, ML & Databricks (Contract)

Randstad Digital Americas; St. Louis (MO); On-site; USD 83,000 - 96,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401K plan

Short-term disability

Life insurance

Job summary

Randstad Digital Americas is seeking a Data Scientist for a long-term contract in St. Louis, MO. The role focuses on building data-driven insights, developing AI/ML solutions, and delivering actionable reports for client services and product enhancements.

Strong Python and Databricks experience are required, with a bachelor’s degree as a baseline qualification. Responsibilities include creating datasets, designing data pipelines, and collaborating with data engineers and analysts to optimize

Qualifications

• ML/data science knowledge required; AI/GenAI experience is a plus but optional.
• Python required; R and other languages not acceptable substitutes.
• Databricks experience is preferred.

Responsibilities

• Generates reports and datasets or report information for end-users using system tools and queries.
• Designs and maintains methods to consolidate and analyze structured and unstructured data for insights.
• Builds machine learning / AI solutions that create measurable value for the business.
• Translates business requirements into data science solutions aligned to goals.
• Works with data analysts to review data pipelines and optimization opportunities.

Skills

AI concepts

Exploratory data analysis

Statistical analysis

Education

Bachelor's degree

Tools

Python

Databricks

Job description

Randstad Digital Americas is seeking a Data Scientist for a long-term contract in St. Louis, MO. The role focuses on building data-driven insights, developing AI/ML solutions, and delivering actionable reports for client services and product enhancements.

Strong Python and Databricks experience are required, with a bachelor’s degree as a baseline qualification. Responsibilities include creating datasets, designing data pipelines, and collaborating with data engineers and analysts to optimize