RapidApply

← All jobs

Senior Machine Learning Engineer, Client Insights

First Mile Group, Inc. · New York, NY telecommuting permitted

Education
Bachelor's in Computer Science, Electrical Engineering, Computer Engineering or a related field
Experience
72 months
Wage
$215,000–$215,000 per year (from the posting)
First / last seen
2026-10-07 / 2026-10-15

Experience must include

statistical and machine learning methodsclassification modelsclustering modelsregression modelsanomaly-detection modelsdata pipelinesPythonSQLadvanced analyticsstatistical modelingdata analysisleading technical projects

Apply

Only apply if you genuinely want this job and meet every stated requirement. RapidApply can check your profile against the requirements and prepare a truthful application packet for you to review — nothing is sent without your approval.

Check my fit & prepare an application

Where this job is advertised

National Labor Exchange (state job banks, via usnlx.com search) swa live
first seen 2026-10-07 · posted 2026-05-30

Original posting ↗

Application instructions (verbatim)

Applicants who are interested in this position may apply https://www.jobpostingtoday.com/ Ref # 41194.

This source's terms don't allow us to republish the full ad; read it at the original posting. Signed-in applicants see the full text on their fit page.

State job banks via NLx, all orders (NY, CA, TX, GA, FL) swa live
first seen 2026-10-08 · posted 2026-05-30

Original posting ↗

Application instructions (verbatim)

Applicants who are interested in this position may apply https://www.jobpostingtoday.com/ Ref # 41194.
Full posting text
Senior Machine Learning Engineer, Client Insights
First Mile Group, Inc. — New York, NY

First Mile Group, Inc. seeks Senior Machine Learning Engineer, Client Insights in New York, NY. Duties: Apply statistical and machine learning methods to develop customer-facing models that support fraud, credit, and compliance decisioning. Design, train, validate, and iterate on classification, clustering, regression, and anomaly-detection models using large and complex datasets. Build and maintain data pipelines and features used for model development and production inference. Collaborate closely with application and data engineers to operationalize machine learning models, including implementing model performance monitoring and retraining mechanisms. Analyze internal and client datasets to generate insights, inform product roadmaps, and improve fraud-detection workflows. Develop optimization models and analytical frameworks to recommend improvements to fraud, compliance, and risk-management processes. Contribute to data governance efforts, including standardizing feature definitions and documenting pipelines, metrics, and model behavior. Partner with engineering and product leaders to provide technical input into roadmap planning and future model-driven product features. Conduct research and bespoke analyses to support new customer use cases and the development of new data science products. Position requires a Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering or a related field or equivalent plus 6 years of experience in the job offered or a related occupation. Additionally, position requires 6 years of experience in modeling and data science. Also requires 3 years of experience in the following: building end-to-end machine learning models; scripting and querying languages (e.g., Python, SQL); advanced analytics, statistical modeling, and data analysis. Requires 2 years of experience in the following: leading technical projects / acting as a technical lead; working with large-scale or unbalanced datasets. Telecommuting permitted. 40 hours/week, $215,000 - $215,000 per year. Must also have authority to work permanently in the U.S. Applicants who are interested in this position may apply https://www.jobpostingtoday.com/ Ref # 41194.

Why we think this is a PERM ad (100% confidence): Rules: PERM-form signals: related_occupation, reference_code, telecommute, degree_field, exact_experience, form_like_headers