GenAI Engineer
The Client
San Antonio, TX, United States
3 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Business Analytics Applications
Data Mining
Relational Databases
Design of User Interfaces
Python (Programming Language)
Machine Learning
Performance Tuning
SAS (Software)
Large Language Models
Deep Learning
Job description
In the assigned Job Role of Data Science Consultant 1, your Area Of Responsibility will be as below:
- Participate in data extraction, transformation, and preparation.
- Resolve common data issues and ensure quality for model development.
- Participate in developing models using statistical or machine learning techniques and collaborate with technology teams to operationalize them into analytics tools or scripts.
- Participate in model testing and validation, selecting the best-performing algorithms based on statistical and business metrics.
- Participate in the development of advanced analytics and machine learning or deep learning models including LLMs using predefined processes and tools like SAS and R/ Python.
- Participate in defining analytics problems; execute visualization, analysis, and predictive modeling with senior support.
- Identify data sources and extract from RDBMS and develop UI/UX for client usage.
- Participate in model performance, while making minor adjustments, and escalate risks or compliance concerns and generate reports on deviations or schedule slippages.
- Proactively participate in detailed documentation of model development, testing, and deployment activities for reproducibility.
- Work closely with business and technology teams to translate requirements into actionable models, while communicating results effectively.
- Apply predefined quality measurement frameworks, if any, to individual project tasks.
- Participate in deploying analytics tools in test and production environment, while ensuring they meet operational requirements.
Requirements
- Strong analytical and problem-solving mindset with hands-on model development skills.
- Ability to translate business needs into actionable analytics solutions.
- Focus on data quality, validation and performance optimization.
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