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Master’s Degree or Ph. D. in Data Science, Operations Research, Psychometrics, Marketing Science, Finance, (Bio)Statistics, Econometrics, Computer Science, Applied Mathematics, or another quantitative field.
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We are seeking an individual with significant project management/technical lead experience and a strong technical background, which may include experience working on frontend or backend web development, data engineering, data analysis, quantitative social science, data visualization, data science, site reliability engineering, or cloud architecture.
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OR Two (2) full academic years of progressively higher level graduate education leading to a graduate degree in a related field of study such as: business administration (finance, accounting, auditing, marketing and business law) law, economics, criminology, political science, government, social science, communications, psychology, public administration or other related field.
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Data Visualization: Create dynamic dashboards and visualizations to communicate omni-channel marketing performance, trends, and insights to stakeholders across the organization. We are seeking a Senior Marketing Data Analyst to join our team and lead data-driven decision-making in our omni-channel marketing initiatives.
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A preference for candidates with a background in Marketing Data Engineering. Innovate and develop database architectures to gather and organize data, enabling the generation of interactive dashboards in business intelligence tools like Tableau for comprehensive marketing analysis.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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As our first Data Science hire focusing on Machine Learning at Circle, you'll start by focusing on two critical problems: helping identify transactions and actors who might be acting illicitly and helping us better balance our reserves across a series of accounts to reduce systemic risk inside the company.
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Applying data science methods (i.e., statistical modeling, machine learning techniques: regression, forecasting / predictive modeling, decision trees) to healthcare and Life Sciences business problems.
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Proficient in data science tools and programming languages such as Python, R, Scala, SQL, and SAS. Work with a variety of data science tools and programming languages such as SAS, Python, R, Scala, SQL.
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Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g., regression, classification, Time Series analysis: e.g., ARIMA, Traditional machine learning methods: e.g., Random Forest, ensemble model techniques, Optimization: e.g. linear programming.
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We are looking to hire a staff machine learning engineer to join our RVO Health data science team. 6+ yrs of professional experience in a data science role with a preference for holding an MS or PhD in STEM with a focus in ML, statistical modeling, or optimization.
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Design, Develop and implement data science projects, including machine learning models, deep learning models, NLP solutions, statistical analysis, and data visualization. The ideal candidate will have a strong background in data science, machine learning, deep learning, NLP, Generative AI and statistical analysis, as well as experience in a leadership role.
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Serve as a climate science subject matter expert, performing meteorological and climate data analysis, including regional climate profiling guiding teams on the use of climate data and tools for assessing natural hazard risk.
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In this role, you will drive strategic thinking and cross-functional alignment around data-driven approaches to optimize product and marketing efforts (including experimentation) based on current state data, historical operational data, entity relationships, lifecycle stages, and other critical attributes or customer needs.
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marketing data science jobs Company: E Solutions in Atlanta, IN, Arkansas
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