Senior ML Architect: Production Models & Data Pipelines

Sedgwick; United States; Remote; USD 175,000 - 220,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k with match

PTO

Job summary

Sedgwick is seeking a Machine Learning Architect to partner with stakeholders and drive advanced analytics and data science initiatives. You will design data models, create algorithms, and share insights to inform business decisions.

The role requires leadership in cross-functional discussions, mentoring team members, and delivering end-to-end data solutions including ETL pipelines and NLP applications in healthcare contexts.

Qualifications

• Master's degree or PhD in a quantitative field preferred.
• 10 years of related experience including 3 years of predictive modeling, data science, and analysis with data wrangling/feature engineering.
• Experience with natural language processing and healthcare data preferred.
• Proficiency writing code in Python or R and documenting for reproducibility.

Responsibilities

• Builds, prototypes, and deploys machine learning models in production environments.
• Collaborates with product, technology, and stakeholders to scope data science projects.
• Communicates modeling challenges, findings, and outcomes to technical and non-technical stakeholders.
• Designs and implements end-to-end ETL data pipelines from multiple data sources.

Skills

Python or R

Data visualization

SQL

Excellent communication

Team collaboration

Problem solving

Education

Master’s degree or Ph.D. in statistics, mathematics, computer science, data science, economics, or related quantitative field

Tools

Python

R

SQL

Data visualization libraries

Job description

Sedgwick is seeking a Machine Learning Architect to partner with stakeholders and drive advanced analytics and data science initiatives. You will design data models, create algorithms, and share insights to inform business decisions.

The role requires leadership in cross-functional discussions, mentoring team members, and delivering end-to-end data solutions including ETL pipelines and NLP applications in healthcare contexts.