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Manage data ETL to analyze the state of our clients’ businesses across a variety of systems, channels and data sources (paid search, display media, website, social media, advertising campaigns, offline media, brand sales and brand equity.
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Advanced proficiency with SQL and data visualization tools (e.g. Tableau, Looker, etc) Partner directly with the Cash App Trust org, working closely with product, operations, engineers, legal and compliance, and machine learning teams.
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The faculty member will establish a research program focused on leveraging machine learning methods to integrate multiple modalities of data (e.g., EHR, imaging, genomics) including environmental exposure data into computational models for prevention, diagnosis, and treatment of breast cancer, and for mechanistic understanding of breast cancer etiology.
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Familiar with modern data warehousing systems, such as Snowflake, and comfortable with deploying and maintaining Machine Learning models in a production environment. We are seeking a highly skilled Senior Data Engineer to help define the next stages of maturity in our data platforms, with a strong emphasis on building and scaling Machine Learning (ML) pipelines.
$199,408 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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In addition, the senior principal scientist will assist in a wide range of activities such as working on complex datasets, developing/recommending novel machine learning tools, data visualizations, quantitative pharmacometric models, disease progression models, mechanistic and empirical Pharmacokinetic-Pharmacodynamic (PK/PD) models, clinical trial simulations, literature meta-analysis using quantitative approaches and statistical modeling of historical and preclinical data.
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The Machine Learning Engineer sits on the Commercial Data Science (CDS)Team within our Strategic Analytics & Intelligence Organization (SAI) and exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively.
$306,800 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics. You will develop and implement image processing pipelines for multiview, multiscale image data generated from our hardware.
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SFO’s sustainability work centers around five primary areas: Energy, Carbon, Waste, Health, and Water, each with bold 2030 goals as described further in SFO’s 2023 Zero Annual Report and SFO’s Strategic Plan. In order to achieve net zero energy and net zero carbon, SFO actively tracks and aggregates utilities (e.g. water, gas, electricity), greenhouse gas emissions (GHG), and advanced energy asset performance data, among other data, in support of a decarbonized future.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
$244,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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You have at least 3+ years of work experience as a data scientist in an analytics role. We are looking for a Product Data Scientist to drive understanding of how our business and its products are scaling and performing.
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This team of computational scientists is responsible for advancing Bristol Myers Squibb's industry-leading pipeline through development and application of cutting-edge tissue-based image analysis approaches, often in multi-modal context (e.g. spatial transcriptomics, combining different imaging modalities or imaging with molecular data.
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They apply standardized data models and mapping to ensure data is accessible for end users in end-to-end user tools through use of APIs. They define and embed best practices and ensure compliance with Quality Management practices and alignment to automated data governance.
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Social Impact: Ten employee-driven Business Resource Groups; two paid volunteer days annually; Environmental, Social and Governance (ESG) initiatives for local and global impact. Learning & Development: LinkedIn Learning access; internal Talent Marketplace with opportunities to work on projects cross-company; Ten Thousand Coffees Thomson Reuters café networking.
$271,700 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Strong computational fundamentals including machine learning, algorithms, data structures, and statistics. Predictive modeling with cutting edge machine learning tools are at the core of this work, exemplified by recent publications modeling regulatory activity as a function of DNA sequence using deep learning.
$162,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago
data governance learning jobs Company: Wex in San Francisco, CA
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2023 Quarterly Review: What’s Happening in Recruitment?
It’s that time again. It’s your quarterly review. Get excited because this is a great time to review some of the amazing accomplishments you and other pros like you have made in recruitment for 2023 thus far! Despite recruitment challenges, things are starting to balance out in the candidate market - partly because of the brilliant ideas and methods being used.
Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
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When Rage Applying Strikes: How to Identify Unserious Candidates
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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The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).
Building a Candidate Pipeline Through Internships
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.