Remote Data Scientist: AI & ML Impact Lead

Ladders; United States; On-site; USD 120,000 - 145,000; Full time

Benefits offered by this job

Diversity & Inclusion Working Groups

Parental Leave Policy

Paid Volunteer Time Off (VTO)

Job summary

Ladders is seeking a Data Scientist to join a leadership team in Enterprise Technology. The role blends data, AI-enabled capabilities, and scalable tech delivery, partnering with business and technical stakeholders across the organization.

You will lead ML/GenAI projects, surface trends, and translate analysis into actionable business metrics. The position is remote for US-based candidates only with a competitive compensation range.

Qualifications

• 5 years of hands-on experience in applied data science, ML, AI engineering, or AI research.
• Bachelor's degree in a technical field strongly preferred.
• Proficient with Python and AI libraries such as Databricks and LLM APIs.

Responsibilities

• Lead applied AI projects from concept to impact, prototype, validate, and help deploy ML and GenAI solutions.
• Act as an internal consultant across teams to scope problems and evaluate approaches.
• Lead the development and deployment of models for use cases like fraud and anomaly detection.
• Design robust experiments and establish evaluation pipelines for model reliability.
• Translate research insights into scalable APIs and tools for other teams.
• Explore new techniques to enhance developer and security experiences.
• Communicate technical concepts clearly to stakeholders.

Skills

Python

ML

AI engineering

Data analysis

Education

Bachelor's in CS

Tools

Databricks

LLM APIs

scikit-learn

OpenAI

Job description

Ladders is seeking a Data Scientist to join a leadership team in Enterprise Technology. The role blends data, AI-enabled capabilities, and scalable tech delivery, partnering with business and technical stakeholders across the organization.

You will lead ML/GenAI projects, surface trends, and translate analysis into actionable business metrics. The position is remote for US-based candidates only with a competitive compensation range.