Applied Scientist II

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 business problems.

Key Job Responsibilities

1. Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML.
2. Collaborate with cross-functional teams to architect and execute technically rigorous AI projects.
3. Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines.
4. Engage in effective technical communication (written & spoken) with coordination across teams.
5. Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility.
6. Publish research papers in internal and external venues of repute.
7. Support on-call activities for critical issues.

BASIC QUALIFICATIONS

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

PREFERRED QUALIFICATIONS

1. 3+ years of building machine learning models or developing algorithms for business application experience.
2. Have publications at top-tier peer-reviewed conferences or journals.
3. Track record of diving into data to discover hidden patterns and conducting error/deviation analysis.
4. Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
5. Exceptional level of organization and strong attention to detail.
6. Comfortable working in a fast-paced, highly collaborative, dynamic work environment.

Posted: October 4, 2024 (Updated 1 day ago)

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