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Mid LevelFull-timePythonAWSGCPAzureMachine LearningData ScienceCI/CDAINLP
Salary Range
$20,400 - $27,600 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a Data Science Architect to join our team. This role involves designing and implementing technical solutions for client business use cases, with a focus on predictive modeling, optimization, and cloud-based data solutions.
Key Responsibilities
- →Understand client business use cases and technical requirements and convert them into technical design
- →Map decisions with requirements and translate them to developers
- →Identify different solutions and narrow down the best option that meets client requirements
- →Define guidelines and benchmarks for NFR considerations during project implementation
- →Write and review design documents explaining overall architecture, framework, and high-level design
- →Review architecture and design on aspects like extensibility, scalability, security, and user experience
- →Develop and design overall solutions for functional and non-functional requirements
- →Understand and relate technology integration scenarios and apply these learnings in projects
- →Resolve issues raised during code/review through systematic analysis of root causes
- →Carry out POCs to ensure suggested design/technologies meet requirements
Requirements
- ✓9+ years of total experience
- ✓Hands-on working experience in data science with a focus on predictive modeling (Statistical Analysis, ANOVA, Time series Analysis, Regression Analysis) and optimization
- ✓Strong working experience with Data Science on GCP, Generative AI fundamentals
- ✓Strong experience with Python (and/or R) and libraries such as Pandas, NumPy, Scikit-learn
- ✓Strong knowledge of Cloud Architecture and deployment of data solutions in cloud ecosystems (AWS, Azure, GCP)
- ✓Proven expertise in machine learning, mathematical optimization (LP, IP, genetic algorithms, RL), and NLP techniques
- ✓Familiarity with Generative AI fundamentals and hands-on experience with RAG, Lang Chain, Llama Index, and prompt engineering
- ✓Strong understanding of MLOps principles and tools for CI/CD, monitoring, and model lifecycle management
- ✓Excellent communication skills and the ability to collaborate effectively with cross-functional teams
