Hi,
Momento USA is a global technology consulting, talent
acquisition, and creative development firm that addresses clients' most
pressing needs and challenges. We are currently looking for a Data Science/Machine
Learning Builder - Minnetonka, Minnesota (On-site). Please let me know if
you are interested.
Role: Data Science/Machine Learning
Builder
Location: Minnetonka, Minnesota (On-site)
Job Description:
- Client
seeks a highly skilled Data Science / Machine Learning Builder to drive
advanced analytics, anomaly detection, predictive modeling, and
production-grade AI solutions across Claims and Payment Integrity,
Customer Service, and Technology workflows.
- This
role emphasizes hands-on delivery of scalable, secure, and maintainable ML
systems in a healthcare context, with a focus on multimodal approaches,
deep learning, and integration into enterprise workflows.
- The
ideal candidate will possess strong technical ownership, production
mindset, and the ability to translate complex business problems into
robust analytical solutions.
- The
position is based in Minnetonka, Minnesota, with hybrid work expectations
and a preference for local talent.
Roles and Responsibilities:
- Data
Science / Machine Learning Builder, Production AI Systems Developer,
Design, build, deploy, and operate production AI, machine learning, and
analytical systems with a focus on claims integrity, customer service, and
technology workflows.
- Develop
and integrate multimodal systems combining structured data, NLP,
embeddings, deep learning, and generative AI for enhanced decision-making
and output explainability.
- Engineer
robust feature pipelines, population/target definitions, model evaluation
frameworks, and scoring architectures with strong emphasis on
explainability, monitoring, and drift detection.
- Collaborate
with MLOps, data engineering, and platform teams to ensure CI/CD,
observability, security, compliance, and auditability of deployed models
and services.
- Own
operational support for ML systems, including troubleshooting, root-cause
analysis, and continuous improvement in production environments.
- Apply
modern software engineering practices including source control, automated
testing, infrastructure as code, containers, and deployment automation.
- Conduct
data discovery, curation, and integration work, including diagnosing and
resolving pipeline issues where necessary.
- Work
closely with AI/Automation and business teams to design end-to-end
solutions that deliver measurable operational and business outcomes.
- Demonstrate
autonomy in ambiguous environments, make sound technical tradeoffs, and
deliver high-velocity, reviewable work.