Lead the planning and design of battery data and algorithm products while driving innovation and ensuring smooth project execution across teams.
Data Product Manager
Responsibilities
Responsible for battery data and algorithm product planning, design and product lifecycle management
Had a deep understanding of battery business, continued business research, planned and designed prototypes of data and algorithm products, and cooperated with business parties and product R&D to implement data products.
Managed and followed up routine iteration projects of data products to ensure the smooth launch of each version
Focus and track the development trends of the same industry at home and abroad, and constantly carry out product model innovation and business iteration
Qualifications
Bachelor’s degree or above, more than 3 years of data or algorithm product experience, with battery industry big data and algorithm product experience is preferred
Proficient in Axure and other product prototype tools; familiar with Tableau, PowerBI, FineBI, SQL and other data analysis tools is preferred
Strong ability of product planning, design and project implementation; responsible for designing data analysis, algorithm, data visualization and other related products is preferred
Familiar with common data analysis and processing methods, have sensitive data awareness, have certain independent data processing ability, familiar with application scenarios of data product solutions in the industry
Have excellent logical thinking and quick learning ability, good communication skills and document output ability, can quickly promote the implementation of data product projects, have strong cross-team cooperation ability and execution ability
SES builds innovative solutions in material discovery and advanced battery management, focusing on accelerating the global energy transition. Our primary customers range from energy companies to tech enterprises looking to enhance their battery technology with machine learning. What sets us apart is our commitment to integrating AI into battery R&D, streamlining the development process and improving efficiency.
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