Collaborate with teams across the business to translate their needs or challenges into machine learning or statistical problems
Collaborate with business, engineering, infrastructure and data science teams to translate their needs or challenges into production-grade Artificial Intelligence (AI) and Machine Learning (ML) deployment architectures for batch, real-time streaming and edge deployments
Integrate Artificial Intelligence & Machine Learning products through common libraries, robust data and Continuous Integration/Continuous Delivery (CI/CD) pipelines, deployment standards and documentation
Support the development of data products through exploratory data analysis, feature engineering and model building
Effectively communicate experiments, models and analytics outputs with partners
Other duties as assigned

Requirements

Bachelor’s degree in Computer Science or a quantitative discipline; OR demonstrated capability to perform job responsibilities with a combination of a High School Diploma/GED and at least four (4) years of previous relevant work experience
Three (3) years of relevant industry experience
Proficiency in Python, SQL, git and common data science and machine learning libraries
Experience building machine learning models
Able to write production quality code and be familiar with software engineering best practices, including testing and version control
Ability to communicate their findings to both technical and non-technical audience
Ability to successfully complete technical interviews and take-home test in areas of statistics, machine learning, SQL, Python, PySpark, optimization and MLOps
Available for overnight travel (10%)
Must pass a pre-employment drug test
Must be legally eligible to work in the country in which the position is located.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonSQLgitmachine learningdata sciencefeature engineeringmodel buildingproduction quality codeMLOpsoptimization

Soft Skills

communicationcollaborationproblem-solvingability to communicate findingsability to work with technical and non-technical audiences