Global Data Scientist — ML & Analytics for Enterprise

Equal Experts; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Equal Experts, a consultancy delivering custom software solutions, seeks a data scientist to work on ML projects for blue-chip clients. You will join teams using modern agile practices to deliver iterative models and insights.

You'll apply Python and ML frameworks to build production-ready models, collaborate with data engineers and BI teams, and communicate findings to non-technical stakeholders while working with globally distributed teams.

Qualifications

• Strong analytical experience with data from multiple angles and business context.
• Significant experience building machine learning products.
• Proficiency in Python and ML frameworks such as Scikit-Learn or TensorFlow.
• Experience with SQL and data querying.
• Experience with Git and CI/CD tools.
• Ability to communicate with data engineering or BI teams and work in ML Ops.
• Excellent collaboration and communication for remote, distributed teams.

Responsibilities

• Use data to improve client decision-making and customer experience.
• Uncover insights from large data repositories and provide tactical guidance.
• Drive adoption of ML outputs across business partners to create value.
• Develop quantitative models using machine learning and data analysis.
• Collaborate in an agile environment to deliver ML increments.
• Ensure timely delivery across supporting teams to meet goals.
• Promote best practices and standards across client teams.

Skills

Analytical skills

Machine learning products

Python

SQL

Git & CI/CD

Team collaboration

Remote communication

Tools

Scikit-Learn

TensorFlow

Git

CI/CD tooling

SQL tooling

Job description

Equal Experts, a consultancy delivering custom software solutions, seeks a data scientist to work on ML projects for blue-chip clients. You will join teams using modern agile practices to deliver iterative models and insights.

You'll apply Python and ML frameworks to build production-ready models, collaborate with data engineers and BI teams, and communicate findings to non-technical stakeholders while working with globally distributed teams.