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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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The Principal Data Scientist / Applied Machine Learning Scientist Computational Advertising is a critical data science/applied machine learning role that uses cutting-edge machine learning, deep learning, big data mining and optimization techniques to solve the challenging problems from ads relevance, ranking to campaign optimization.
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The ideal candidate will have a mix background with data engineering, data science, and machine learning engineer. Proficient in advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA), Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis), Decision Tree techniques (e.g., CART, CHAID.
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Experience in two or more applicable data science disciplines: statistical modeling, machine learning, data mining, time series data analysis, or data engineering.
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The Marketing Decision Science team focuses on developing data-driven models and services to bringing high-quality demand from offsite digital sites to Walmart E-Commerce sites at low cost in order to sustain and accelerate the growth of Walmart E-Commerce and ultimately cultivate a large loyal base of omni-channel customers who view Wal-Mart as their top choice of retail shopping.
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Design and apply advanced modeling solutions in the areas of statistical analysis, bioinformatics, data automation, data mining, machine learning and/or data visualization.
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Customer Behavior Modeling: Lead efforts to analyze customer behavior patterns and preferences through data mining, machine learning, and predictive analytics. Demonstrated experience in data science, machine learning, and advanced analytics, with a track record of applying these skills to customer engagement or marketing metrics in the pharmaceutical or healthcare sector.
$232,220 - $300,520 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Experience working with large-scale data mining and reporting tools (examples: SQL, MS Access, Essbase, Cognos) and other financial systems (examples: Oracle, SAP, Lawson, JD Edwards) The successful candidate will be a self-starter with strong interpersonal and communication skills, data mining and modeling capabilities, keen attention to detail, sound logical reasoning, and the ability to manage multiple projects effectively.
$56,900 - $128,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise with efficient data manipulation techniques with various data mining and machine learning methods applied to geospatial “Big Data”, data with large volume, high velocity, high variability, and changing definitions.
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Experience in one or more data science languages, or toolkits such as R, MATLAB, Python, numpy, pandas, scikit-learn, TensorFlow, etc. Serve as a cross-product expert, providing technical guidance in Machine Learning, Natural Language Processing, Information Retrieval and Data Mining experiments and projects.
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Research in topics closely related to machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval, or computer vision.
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You must have strong technical depth and experience in application of Machine Learning, Deep Learning, and Data Science techniques. Broad knowledge across the entire data science lifecycle, including data engineering, statistics and governance.
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You will develop predictive models on large-scale datasets to address various business problems leveraging advanced statistical modeling, machine learning, or data mining techniques. Strong understanding of computer science fundamentals such as algorithms, data structures and run-time analysis.
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Identify business problems and solve them by using various numerical techniques, algorithms, and models in Operations Research, Data Science, and Data Mining. Bachelor's or Masters degree in Operations Research, Supply Chain Management, Computer Science, Systems Engineering, Mathematics, Statistics, Quantitative Finance, or related field and 5 years of work experience in any analytics-related occupation.
$65 - $70 an hourExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Candidates should have c omputational linguistics and/or data mining experience. Proficiency in statistical analysis of clinical research data using data science programming languages such as Python and R.
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data science mining jobs in Palo Alto, CA
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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.