Overview
On Site
BASED ON EXPERIENCE
Contract - W2
Contract - Independent
Skills
Telecommunications
Design Of Experiments
Taxes
Python
Clustering
Regression Analysis
Predictive Analytics
Natural Language Processing
Algorithms
Data Science
Amazon Web Services
Customer Engagement
Stakeholder Management
Communication
Analytics
Predictive Modelling
Machine Learning (ML)
Optimization
Analytical Skill
Unstructured Data
Modeling
Performance Monitoring
Job Details
We have a fast-moving Machine Learning Developer opportunity in Seattle. This ML professional will help Telecom customer. We have spoken to few resources but didn't qualify. I have shared details here. Please review and let me know if you are available.
If you are not available, please refer any of your friends who are in need of opportunity. Thank you!
Role: Machine Learning Engineer
Location: Seattle, WA - Onsite
Duration: 12 Months
Rates: DOE
Prefer Locals
Visa type: Any
Tax terms: All
Interview: Two rounds
Experience required: 8 years
Roles & Responsibilities
If you are not available, please refer any of your friends who are in need of opportunity. Thank you!
Role: Machine Learning Engineer
Location: Seattle, WA - Onsite
Duration: 12 Months
Rates: DOE
Prefer Locals
Visa type: Any
Tax terms: All
Interview: Two rounds
Experience required: 8 years
- Python, AWS, ML Model Development, Validation, Model Performance monitoring
- ML experience in clustering, regression, other ML related like predictive analytics, scoring algorithm
- Build predictive models, LLMs, NLP models, and machine-learning algorithms to Client insights, trends, and patterns
- Model Performance monitoring
- Model feature development, Graph model development
- Ability to analyze/understand the model development life cycle from business perspectives and provide end to end data science consulting
- Experience of delivering machine learning models in AWS
- Customer engagement and Stakeholder management
- Strong & Assertive communication skills
Roles & Responsibilities
- Partners with business team to understand business problems and objectives Conducts sophisticated analytics using predictive modeling, machine learning, simulation, optimization, and other techniques to deliver insights or develop analytical solutions to achieve business objectives
- Use large amounts of both structured and unstructured data (internal and external) to build Al/Client modeling solutions.
- End-to end experience of model development life cycle including model performance monitoring and model feature development.
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