1 день назад
Data Scientist II (AI/ML)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist II (AI/ML): Developing and deploying machine learning models, analytical solutions, and AI capabilities within a cloud-native data ecosystem with an accent on forecasting, experimentation, model evaluation, and responsible AI. Focus on building AI workflows with AWS Bedrock, AWS SageMaker, Snowflake, Hex, and MLflow, while solving complex problems in feature engineering, benchmarking, explainability, and fairness monitoring.
Location: San Antonio, Texas, United States; full-time onsite role
Company
develops business and client solutions supported by a modern cloud-native data ecosystem and enterprise AI/ML platforms.
What you will do
- Design, develop, and deploy machine learning models for forecasting, segmentation, classification, anomaly detection, and other business problems.
- Contribute to Clara, the AI decision assistant, through context engineering, prompt development, and model evaluation.
- Build experimentation and MLOps workflows using Hex, AWS SageMaker, MLflow, Snowflake, and Intelligence.
- Conduct exploratory data analysis and feature engineering on structured and semi-structured data from the governed Bronze–Silver–Gold architecture.
- Develop evaluation test cases, benchmark models, and contribute to scoring frameworks and quality assurance.
- Apply responsible AI practices, including bias detection, explainability, fairness monitoring, and data privacy compliance.
Requirements
- Master’s degree in computer science, data science, statistics, mathematics, or a related quantitative field; 5+ years of equivalent professional experience may substitute.
- At least two years of progressive experience in data science, analytics, or machine learning.
- Proficiency in Python and SQL, with working knowledge of TensorFlow, PyTorch, scikit-learn, or equivalent frameworks.
- Experience deploying models on cloud AI/ML platforms, preferably AWS SageMaker, AWS S3, and Snowflake.
- Experience with MLflow, experiment tracking, model versioning, statistical modeling, hypothesis testing, and experimental design.
- Strong communication skills, independent judgment, and the ability to lift 20 lbs. of files, supplies, documents, or related items.
Culture & Benefits
- Collaborative environment focused on continuous learning, empirical rigor, and professional growth.
- Competitive overall compensation package and work-life balance.
- Healthcare coverage options and traditional and Roth 401(k) retirement plans.
- Career enhancement opportunities, continuing education, certifications, Leadership Academy, and Mentor Program.
- Employee engagement activities, recognition awards, service awards, and a wellness program.
- Substance-free workplace with pre-employment drug testing; tobacco users are not hired where permitted by law.
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