Infosys is seeking a Senior Lead Data Science Analyst with machine learning and Python experience. Ideal candidate will work on productionizing machine learning models and guide development team for implementing end to end machine learning use case. One will also have the opportunity to shape value-adding consulting solutions for clients by connecting various functions of cloud components. The candidate will provide technology consulting for defining right Data Science and ML use cases. You will contribute to the development and deployment of innovative Analytics and AI solutions.
Required Qualifications:
- Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
- Candidate must be located within the commuting distance of Birmingham, AL or be willing to relocate to the area. This position may require travel in the US.
- All applicants authorized to work in the United States are encouraged to apply
- At least 4 years of experience in Information Technology
- At least 3 years of experience in SnowFlake and ML Ops
- Proven experience in Python and Data Science
- Strong experience in using Python Data structures
- 1+ years of Strong experience in GEN AI RAG Models,
- Experience in developing and implementing algorithms to automate data cleaning, normalization, and enrichment processes
- Understanding the key metrics for validation of the models such as such as mAP, F1-score, and IoU
- Ability to write clean and reusable code that can be easily maintained and scaled
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- Familiarity with cloud platforms (AWS, GCP, Azure).
- 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 of Business and Technology teams
- Experience and desire to work in a global delivery environment