Data Science Analyst- R Programming

About the Role

Key Responsibilities

• Work on productionizing machine learning models and guide development team for implementing end-to-end machine learning use cases.
• Shape value-adding consulting solutions for clients by connecting various functions of cloud components.
• Provide technology consulting for defining right Data Science and ML use cases.
• Contribute to the development and deployment of innovative Analytics and AI solutions.

Requirements

• Bachelor's degree or foreign equivalent from an accredited institution, or three years of progressive experience in the specialty in lieu of every year of education.
• Located within commuting distance of Jersey City, NJ, or willing to relocate; may require travel in the US.
• All applicants authorized to work in the United States are encouraged to apply.
• At least 7 years of experience in Information Technology.
• At least 4 years experience in ETL development and SQL.
• At least 3 years experience in R programming.
• Experience in model deployment using Bitbucket.
• At least 2 years of experience in machine learning, Data Science, deep learning, NLP.
• Familiarity with Python and Data Science.
• 3+ years of experience in GEN AI RAG Models.
• Experience in developing and implementing algorithms to automate data cleaning, normalization, and enrichment processes.
• Understanding key metrics for validation of models such as mAP, F1-score, and IoU.
• Ability to write clean and reusable code that can be easily maintained and scaled.

Nice to Have

• Familiarity with cloud platforms (AWS, GCP, Azure).
• At least 4 years of experience in SnowFlake and ML Ops.
• Stay up-to-date with the latest research and advancements in AI, Image processing, and Computer Vision.
• Familiarity with deep learning frameworks (PyTorch, TensorFlow) including OpenCV.
• Strong communication and analytical skills.
• Ability to work in teams in a diverse, multi-stakeholder environment comprising Business and Technology teams.
• Experience and desire to work in a global delivery environment.

Qualifications

• Educational qualifications as specified in the requirements.
• Experience with relevant tools and technologies.