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Experience with data and analytical tools, such as SQL and Power BI. R, Python and Adobe Analytics a plus. Additionally, the MAC Lead will be exposed to the ins and outs of developing data strategies for predictive analytic applications, fundamental skills of big data, data science and statistical learning methods, and agile delivery methodologies.
$166,465 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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At least 5 years' experience in Python, Scala, or R for large scale data analysis. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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The Senior Big Data Engineer will be responsible to employ various tools and techniques to construct frameworks that prepare information using SQL, Python, R, Java and C. The Senior Big Data Engineer will be responsible for employing machine learning techniques to create and sustain structures that allow for the analysis of data while remaining familiar with dominant programming and deployment strategies in the field.
Full-timeRemoteExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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Background with Data Science tools such as R, Python, and SAS is a plus. Experience with Azure cloud computing, including big data technologies such as Azure Databricks cluster management.
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PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics At least 1 year of experience working with AWS At least 1 year of experience managing people At least 5 years’ experience in Python, Scala, or R for large scale data analysis At least 5 years’ experience with machine learning.
Full-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Experience with big data computing on a public cloud platform (e.g. Spark, AWS) is a plus. As a Research Associate, within the JPMorgan Chase Institute, you will conduct economic research using proprietary big data within JPMorgan Chase, under the direction of a Research Lead or Director to deliver quality, rigorous analysis and insights.
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1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience.
$206,800 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R. Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive.
$206,800 a yearFull-timeExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Some general programming knowledge (SAS, R, STATA, VBA, SQL, or Python is a big plus) While Consultants will regularly process data and perform empirical work, they will also be expected to develop a sense of the big picture for each case and to learn how to shape findings into a coherent story supported by prevailing economic theories and statistical methods.
$101,000 a yearFull-timeExpandApply NowActive JobUpdated 25 days ago
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As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
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