Data Scientist JD Discussion:
Inperson interview
45 roles
Any visa fine
Redwood City, CA, USA
Hypothesis, identifying what type of models to build
Build multiple models
Test the models
Refine and fine tune the models
This is not data analytics. They need to be pure data scientists
Responsibilities:
Driving adoption of Deep Learning systems into next-generation.
Designing and deploying Machine Learning algorithms for industrial applications such as fraud detection and predictive maintenance.
Collaborating with data and subject matter experts and its customer teams to seek, understand, validate, interpret, and correctly use new data elements.
Qualifications:
MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields.
Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning).
Experience with prototyping languages such as Python and R.
Strong mathematical background (linear algebra, calculus, probability and statistics).
Experience with scalable ML (MapReduce, streaming).
Ability to drive a project and work both independently and in a team.
Smart, motivated, can-do attitude, and seeks to make a difference.
Excellent verbal and written communication.
Preferred Qualifications:
Experience with JavaScript and Java.
Experience with time series and dynamical systems.
A portfolio of projects (GitHub, papers, etc.).
Cognizant provides excellent benefits and a competitive compensation package.
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