
Consumable Sales-Shandong
Agilent TechnologiesJob Description
• 销售仪器耗材和消耗品,如色谱柱、样品制备和耗材等核心产品,覆盖指定区域。
• 积极响应客户需求,执行销售计划,推动业务增长。
• 有效开拓目标业务的新客户,深入渗透关键客户群体,识别潜在商机。
• 制定明确的销售目标,并寻找方法完成销售任务。
• 化学、食品、制药或相关专业本科及以上学历。
Qualifications
• 3年以上工作经验,熟悉色谱、质谱等分析仪器,有相应产品销售经验优先。
• 具备良好口头和书面表达能力。
• 富有创造力且以结果为导向。
• 能够独立完成销售任务,同时注重团队协作。
• 能够接受一定程度的出差。
Additional Details
This job has a full time weekly schedule.
Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations
Agilent Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.
Travel Required:
50% of the Time
Shift:
Day
Duration:
No End Date
Job Function:
Sales
Opens the company's application page
Listed via
Jobicy
jobicy.com
Similar roles
Design & Tech
Related reads from TCHNX

How Passive Data Collection is Reshaping UX Research
As users grow weary of surveys and interviews, researchers are turning to ambient behavioural signals from keystroke dynamics to micro-interactions to understand product experience without asking a single question.

Why Gen Z is Rejecting Performative Productivity
After a decade of glorifying the grind, a cultural shift is underway. Young professionals are abandoning side hustles not out of laziness, but as an act of resistance against late capitalism's demand for constant monetization.

The Inference Economy: Why AI’s Biggest Cost Shift Is Happening After Training
A major shift in AI economics is reshaping the industry. As training frontier models becomes more expensive and inference becomes dramatically cheaper, companies are being forced to rethink how they build, deploy, price, and monetise intelligent systems.


