数据科学家
Data Scientist
关于决策,激励创造力和推动发展,我们真的相信数据的力量。通过现代数据分析,我们简化了大量数据并得出洞察力的结论,从而证实了我们的领导地位。我们正在寻找一个有热情和能力的数据科学家加入我们的团队,帮助我们发现趋势,解决困难的问题,并引导我们的战略以基于数据的决定。我们在寻找一个准备为我们的团队做贡献并产生影响的数据爱好者:总结:在数据和战略的交叉点上运作,应用你的分析才能来获得见解,构建预测模型和推动决策将有助于你成为数据科学家。在多学科团队工作时,你的责任包括识别业务面临的问题,编译相关信息,并创建解决这些问题和提高绩效的模型。你的努力将塑造我们业务方向,以更好地做出更知情的决定。重要目的:对趋势,模式和联系进行大数据集的分析将帮助你的业务找到实用的见解。为了处理挑战性问题,创建和运行统计模型,机器学习方法和预测分析。一旦你了解业务利益相关者的目标和要求,就从这些中创造数据驱动的解决方案。与分析师和工程师合作帮助你加强数据管道和框架。创建并执行实验,模拟和 A/B 测试以测试概念和改进公司战略。制作有趣的图像来展示观众既具有技术理解又无需复杂的数据见解。创建和更新报告和仪表板监控关键企业数据点。在所有项目上,维护准确度,质量和数据完整性。保持数据科学,机器学习和分析领域的最新新闻可以帮助你保持你的方法和方法当前。所需的商品:申请人必须是美国永久居民或合法公民。强数学,统计学,数据科学,计算机科学或紧密相关领域 (士或博士学位建议).三年以上的相关就业经验作为数据科学家或类似的工作体验,理想情况下伴随着一个工作组来突出。SQL,R 或 Python 知识是必要的;具有大数据系统的经验;
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Regarding decisions, inspiring creativity, and driving development, we really believe in the power of data. By means of modern data analytics, we streamline mountains of data and derive insightful conclusions, therefore confirming our leadership in [industry]. We are looking for a Data Scientist that is passionate and competent to join our team and help us to uncover trends, solve difficult problems, and guide our strategy with data-driven decisions. We are looking for a data enthusiast ready to contribute to our team and have impact.
List of duties: summary Operating at the junction of data and strategy, applying your analytical talents to derive insights, build predictive models, and drive decision-making will help you to be a Data Scientist. Working in multidisciplinary teams, your responsibilities will include identifying problems the business faces, compiling pertinent information, and creating models to solve those problems and raise performance. Your efforts will shape the direction of our business toward better, more informed decisions.
Important Purposes:
Analyzing large data sets for trends, patterns, and linkages will help your business find practical insights.
To handle challenging problems, create and run statistical models, machine learning methods, and predictive analytics.
Once you understand the objectives and requirements of the business stakeholders, create data-driven solutions from those.
Working with analysts and engineers helps you to strengthen data pipelines and frameworks.
Create and perform experiments, simulations, and A/B testing to test concepts and improve company strategy.
Make interesting images to show audiences both with and without technical understanding complex data insights.
Create and update reports and dashboards to monitor key corporate data points.
Over all projects, uphold correctness, quality, and data integrity.
Keeping up with the most recent news in data science, machine learning, and analytics can help you to maintain your methods and approaches current.
Goods required:
To apply, candidates have to be permanent residents or legal citizens from the United States.
strong in mathematics, statistics, data science, computer science, or a closely allied field ( Master's or Ph.D. advised).
Three years or more of pertinent employment experience as a data scientist or similar, ideally accompanied by a body of work to highlight.
Knowledge of SQL, R, or Python is necessary; experience with large data systems like Hadoop or Spark is a benefit.
competent in applying several machine learning models and libraries like Keras, TensorFlow, and scikit-learn.
strong grasp of statistics, data visualization techniques, and experimental design.
Mastery of large data collections, data cleansing and transformation, and data wrangling.
Excellent writing and verbal skills; proficient in both layperson and expert explanation of difficult results.
Having dealt with clouds like AWS, GCP, or Azure would be a benefit.
Data scientists are driven by an unquenchable curiosity and a passion of solving problems.
Rendered Services:
Work flexible hours from anywhere.
Competitive and thorough pay scale and benefits package.
the opportunity to develop one's skills and propel forward in their profession.
Workplace norms supporting diversity, innovation, and teamwork.
Having the chance to support creative, practically significant data science projects.
Originally posted on Himalayas