专业要求：
学历要求：大专及以上
工作经验：不限
薪资待遇：面议
招聘人数：5
招聘对象： 社会人才
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工作地区： 西安市 学历要求：不限性别要求：不限
工作经验：不限薪资待遇：4-8 月薪招聘人数： 1
公司性质：公司规模：所属行业：IT行业-计算机、互联网、通讯、电子、仪器仪..
职位描述：
岗位职责：1、有效的维护并拓展招聘渠道；2、负责整个招聘进程、跟踪面试结果；3、人员招聘、留存的情况跟踪及分析、以便对招聘活动进行有效的评估；4、和候选人洽谈offer，跟踪入职；5、做好员工转正前的日常管理维系工作，协助本部及各部门相关工作； 任职要求：1、大专以上学历，具有一年以上工作经验，有IT公司软件工作招聘经验者优先；2、有非常强的责任心和自驱力，有快速、主动学习新技能的能力；3、性格开朗，有亲和力，热爱招聘工作；4、有一定的抗压能力； 福利待遇：1.有竞争力的薪资:基本薪资+绩效+奖金2.多维的福利体系:入职即购买五险一金、周末双休、8小时弹性工作，节日福利、年终奖，团建活动3.完善的成长体系:能力拓展、多向灵活的成长通道; [详情]
我要投递简历
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工作地区： 上海 学历要求：硕士及以上性别要求：不限
工作经验：不限薪资待遇：2-4 月薪招聘人数： 1
公司性质：公司规模：所属行业：IT行业-计算机、互联网、通讯、电子、仪器仪..
职位描述：
Responsibilities Use predictive/statistical modeling and related methods to build world-class, scalable models that will provide high business value. Apply advanced statistics and data mining techniques to analyze and make insights from big data, such as historical production data and simulation/experiment results. Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements that can realize these improvements. Create software operational machine learning systems to integrate with commercial software.Basic Qualifications Master’s degree in statistics, mathematics or computer science or minimum 7 years’ equivalent job experience Minimum 7 years’ experience in one or more of the following:o statistical programming language (preferably Python, Scala, R or MATLAB/Octave),o data management (SQL, ETL , Data Factory, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets, o developing predictive/machine learning models. Strong English verbal/written communication (CET 6 or equivalent experience) & data presentation skills, including an ability to effectively communicate with both business and technical. Experience with large scale analytics paradigms (Map Reduce, NoSQL). Knowledge with supervised learning methods (linear and logistic regression, generalized linear models, decision trees, random forests, support vector machines, graphical models, neural networks, anomaly detection etc.). Knowledge with unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components, etc.). Very strong self-learning skills. Ability to pick up and adapt modeling methods from other disciplines or leverage methods from other skilled colleagues in other departments in solving problems. Strong organizational, time management, communication, and engineering skills are necessary. [详情]
我要投递简历