Data Scientist, Feature Engineering

35~40K CNY/Per month

Full-time
3~5 years
Refresh at 3 years ago
69 Views
5 Apply
Shanghai
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Job responsibilities
Key Responsibilities - As a data scientist, you are enthusiastic to build the data foundation to support advanced machine learning, including developing, implementing and auditing advanced variables and features - Responsible for building/maintaining alerts, dashboards, and metrics to monitor availability and quality of live data, features and models - Master with large volumes of data; extract and manipulate large datasets using standard tools such as SQL, Spark, and Python - Collaborate with other data scientists and analysts to formulate innovative solutions for advanced features and models - Partner with product and engineering team in implementing features and models, and enhancing systems - Lead and support various ad hoc projects, as needed Minimum Qualifications - Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics or equivalent practical experience - 3+ years of hands-on experience extracting and manipulating large data - 2+ years of experience with scripting in SQL, Python - Experience building visualizations using large datasets and multiple data sources
Job Requirements
Preferred Skills/Experience:Preferred Qualifications - Masters or PhD in Computer Science, Engineering, Mathematics, Statistics or equivalent practical experience - Self-starter, motivated by a passion for developing the best possible solutions to problems - Intellectually curious and comfortable operating in a fast-paced, ever-changing environment - Exceptional time management skills; has the ability to multi-task and triage the evolving responsibilities of the role - Superb communication and organization skills, with the ability to simplify and present complex engineering and analytical concepts to an executive audience - Understanding of modern machine learning techniques is an advantage but not essential - Work experience in risk or payments is an advantage but not essential.
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