Senior Applied Scientist, Digital Acceleration

DESCRIPTION
The Digital Acceleration (DA) team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms for solving Digital businesses problems.
Key job responsibilities
– Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML.
– Collaborate with cross-functional teams to architect and execute technically rigorous AI projects.
– Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines.
– Engage in effective technical communication (written & spoken) with coordination across teams.
– Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility.
– Publish research papers in internal and external venues of repute
– Support on-call activities for critical issues

BASIC QUALIFICATIONS
– Experience building machine learning models or developing algorithms for business application
– PhD, or a Master’s degree and experience in CS, CE, ML or related field
– Knowledge of programming languages such as C/C++, Python, Java or Perl
– Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
– Proficiency in coding and software development, with a strong focus on machine learning frameworks.
– Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
– Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team setting.

PREFERRED QUALIFICATIONS
– 5+ years of building machine learning models or developing algorithms for business application experience
– Have publications at top-tier peer-reviewed conferences or journals
– Track record of diving into data to discover hidden patterns and conducting error/deviation analysis
– Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
– Exceptional level of organization and strong attention to detail
– Comfortable working in a fast paced, highly collaborative, dynamic work environment

Basic Qualifications

– 5+ years of building machine learning models for business application experience
– PhD, or Master’s degree and 10+ years of applied research experience
– Experience programming in Java, C++, Python or related language
– Experience with neural deep learning methods and machine learning

Preferred Qualifications

– Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
– Experience with large scale distributed systems such as Hadoop, Spark etc.

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