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Social Finance, LLC seeks Staff Data Scientist in San Francisco, CA:
Job Duties: Identify high impact business opportunities to help members achieve their financial goals. Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation. Develop and apply machine learning models to solve business problems. Evaluate and interpret the results of data analysis. Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and nontechnical stakeholders. Design and implement data collection. Build data pipelines to deploy production level datasets. Collaborate with cross functional teams and business leader to understand needs and offer data driven solutions. Participate in internal team Knowledge sharing session and willingness to mentor junior Data Scientists in the team. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA.
Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and three (3) years of experience in the job offered or related occupation.
Special Skill Requirements: (1.) Artificial Intelligence (AI) & Machine Learning (ML); (2.) Natural Language Processing (NLP); (3.) Time Series Forecasting; (4.) ETL Pipelines; (5.) AWS (Sagemaker, S3, EMR); (6.) Advanced clustering; (7.) Data Visualization; (8.) A/B testing; (9.) Collaboration with cross-functional partners; (10.) Leadership. Any suitable combination of education, training and/or experience is acceptable. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA.
Salary: $250,080.00 - $275,088.00 per year.
Submit resume with references using the apply button on this posting or by email to: Req.# 1014.323.2** **at: ATTN: HR, jobadverts@sofi.org.
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Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
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