Data Science Expert - Fully Remote | Upto $70/hr

United States Digital Space LLC; United States; Remote; USD 83,000 - 96,000; Part time

Job summary

Mercor is hiring Data Science and Analytics Experts on a contract basis. Remote position focusing on building enterprise data science scenarios for large-scale predictive modeling and multi-stakeholder analytics governance at Fortune 500 accounts.

You will work with Snowflake, Databricks, Python/R, SQL, Tableau/Power BI, and platforms like SageMaker and Vertex AI. Ideal candidates have 5+ years as data scientists or ML engineers, with direct ownership of production data products and deep

Qualifications

• 5+ years as a data scientist, analytics leader, or ML engineer at an enterprise org.

Responsibilities

• Construct enterprise data science scenarios for large-scale predictive modeling and analytics governance.
• Build analytics tasks across ML model development, data pipelines, and BI at scale.
• Develop data and MLOps scenarios using enterprise tools and platforms.
• Apply enterprise data science methodologies, including A/B testing and MLOps best practices.
• Auth credits to distinguish authentic enterprise data science judgment.

Skills

Data science

Analytics leadership

ML engineering

Tools

Snowflake

Databricks

Python

R

SQL

Tableau

Power BI

SageMaker

Vertex AI

MLflow

Job description

About the jobMercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Science and Analytics ExpertsType:ContractCompensation:$60–$70/hourLocation:Remote

Role Responsibilities

• Construct enterprise data science scenarios for large-scale predictive modeling and multi-stakeholder analytics governance at Fortune 500 accounts.
• Build analytics tasks across machine learning model development, enterprise data pipelines, and business intelligence at scale.
• Develop data and MLOps scenarios using tools like Snowflake, Databricks, Python/R, SQL, Tableau/Power BI, and enterprise ML platforms such as SageMaker, Vertex AI, and MLflow.
• Apply enterprise data science methodologies, including statistical rigor, A/B testing frameworks, and MLOps best practices to produce reference analyses and executive-level insights.
• Author rubrics that distinguish authentic enterprise data science judgment from generic textbook recall.

Qualifications

Must-Have

• 5+ years working as a data scientist, analytics leader, or ML engineer at a Fortune 500 technology or enterprise organization.
• Direct ownership of F500 data products, analytics initiatives, or machine learning systems in production.
• Fluency in enterprise data science tooling and methodologies, with an understanding of F500 data governance and privacy compliance.

Preferred

• Prior rubric, technical curriculum, or model documentation authorship.