Data Scientist VP – Chief Data Office India - Exp: (10-15 years) IC Role -Mumbai
Our client is looking for a Data Scientist with the Chief Data Office, who would be responsible to shape the future of the Chief Administrative Office and its businesses by applying world-class machine learning expertise.
Responsible to use data and analysis to identify and solve biggest challenges and develop state-of-the art machine learning models to solve real-world problems.
Ability to collaborate on a wide array of products and business problems with a diverse set of cross-functional partners across Finance, Supplier Services, Data Security intelligence program, Global Real Estate and Customer Experience.
Develop codes and own ML products to drive business outcomes and influence strategic partners, in a highly collaborative environment.
Master’s in quantitative field (Computer Science, Mathematics, Statistics, or ML)
6-8 years industry experience in data science coding / applied ML model development (must have)
Strong knowledge and experience with Traditional ML, Deep Learning, NLP, time-series predictions, or recommendation systems (must have)
Excellent python coding and algorithm skills (must have)
Experience with data visualization techniques and software
Strategic thinker with demonstrated problem-solving skills using Machine Learning
Foundational Statistics knowledge
What is in it for you-
A stimulating working environment with equal employment opportunity.
Growing skills while working with industry leaders and top brands.
Reach us- If you feel that you are the right fit for the role please share your updated CV at firstname.lastname@example.org
Disclaimer- Crescendo Global specializes in Senior to C-level niche recruitment. We are passionate about empowering job seekers and employers with an engaging memorable job search and leadership hiring experience. Crescendo Global does not discriminate on the basis of race, religion, color, origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Profile Keywords: Machine Learning, Data Science, Model Development, Traditional ML, Deep Learning, NLP, Time-series