Description

Salesforce Inc. seeks Data Scientist in San Francisco, CA:

Job Duties: Use advanced statistical learning techniques to build and optimize models that predict probabilities of software regression test failures given specific code changes, subject to computational feasibility constraints. Develop clustering models that allow grouping of code failure stack traces using kernel-based approaches and similarity signals. Model end-to-end systems performance based on signals and logs emitted by constituent components and auto-detect anomalous deviations from the system baseline. Develop machine learning models using state-of-the-art techniques and algorithms in the field of artificial intelligence. ˆHQ address additionally encompasses the following Salesforce locations in San Francisco: 350 Mission Street, 415 Mission Street, 50 Fremont Street. The permanent position may be offered at any of these locations in San Francisco. Telecommuting is an option.

Minimum Requirements: Master’s degree (or its foreign degree equivalent) in Mathematics, Statistics, Computer Science, or a related quantitative discipline, and two (2) years of experience in the field of data/program analysis or two (2) years of experience in the job offered.

Special Skill Requirements: (1) Machine Learning (two years); (2) Advanced Statistical Modeling Techniques (two years); (3) Data Analytics; (4) Data visualization; (5) Object-oriented programming; (6) Python; (7) R; (8) SQL; (9) Database management systems; (10) Version control system. Any suitable combination of education, training and/or experience is acceptable. Telecommuting is an option.

Submit a resume using the apply button on this posting or by email at: onlinejobpostings@salesforce.com at Job# 22-16568. Salesforce is an Equal Opportunity & Affirmative Action Employer.

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For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.