Start Date
Immediate
Expiry Date
18 Jun, 25
Salary
0.0
Posted On
18 Mar, 25
Experience
1 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Normalization, Validation, Data Structures, Map, Teams, Travel, Azure, Data Cleaning, Python, Algorithms, Image Processing, Opencv, Information Technology, Analytical Skills, Key Metrics, Snowflake, Computer Vision
Industry
Information Technology/IT
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:
Preferred Qualifications:
The job may entail extensive travel. The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.
ABOUT US
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Please refer the Job description for details