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As needed, collaborate with internal and external stakeholders to identify object detection, optical character recognition, automation, predictive modeling, pattern analysis, natural language processing, fraud detection, and other business cases for using ML.
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The LCRR Regional Lead will work closely with the Specialized Solutions group to apply dashboarding capabilities, advanced data analytics, and machine learning for predictive modeling of SL material identification but will not be responsible for development of these tools.
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Tasks may include assisting with the analysis, development, and design of processes and infrastructure relating to water supply, stormwater facilities, irrigation facilities, culverts, hydrology, open channel hydraulics, bridge hydraulics, floodplain modeling/mapping, hydrologic/hydraulic modeling, river/stream/habitat restoration and fish passage, pollution control and treatment, and preserving the quality of the environment by averting the contamination and degradation of water resources.
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The Senior Data Scientist will be responsible for the development and implementation of predictive modeling algorithms and techniques to solve complex business problems and optimize member experiences.
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Advanced Analytical Skills: Proficiency in statistical analysis, data mining, and predictive modeling. We solve many exciting challenges including customer acquisition, customer activation and retention as well as media mix modeling, marketing attribution and experimentation.
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You will build and lead a team of SDS data scientists, who employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency.
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As an SDS machine learning engineer, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.
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Develop architectures that enable scalable data extraction and transformation for both predictive and prescriptive modeling. Experience with infrastructure tools such as Terraform, Kubernetes, Docker, Github CI/CD, AWS/GCP, cloud native technologies.
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Demonstrated understanding of business and the importance of reporting, business intelligence, predictive analytics, and financial modeling. Environment: Visual Studio, JIRA, Confluence, Bitbucket, Bamboo, SQL Server Management Studio, Amazon RDS, Amazon EC2, Amazon EBS, and Windows Server.
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Experience with some or all of the following: data mining, predictive modeling, statistics, experimental design, application development, computational analytics, econometric modeling, data visualization.
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Use data science and machine learning to develop effective predictive models. 5+ years of experience with machine learning, statistical modeling, and optimization techniques. The ideal candidate will have a passion for using machine learning tools and techniques to construct, optimize, and evaluate predictive models that predict the likelihood of different business outcomes.
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Design, develop, and implement cutting-edge AI algorithms that enable predictive analytics, intelligent decision-making, and process automation within the HCM and Payroll domains. Familiarity with statistical modeling techniques, AI frameworks (e.g., TensorFlow, PyTorch), and AI tools (e.g., scikit-learn, spaCy.
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Experience in analytics, advanced analytics/statistics, predictive modeling. About the job Insights & Data Analyst- Remote. Working knowledge of analytics and statistical software such as SQL, R, Python, Excel, Power BI and others to perform analysis and interpret data.
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Knowledge of optimization and predictive modeling techniques and experience applying them to real-world problems. Strong understanding of data modeling and statistical analysis. Partner with engineers, product managers, and business partners to identify algorithmic problems, brainstorm possible approaches, and recommend the best path forward.
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In the alternative, at least a bachelor’s degree in Computer Science, Computer Information Engineering, Data Science, or a related field and at least 5 years of prior progressive experience as a Data Scientist or in a related role using Operations Research and Continuous Simulation modeling would be acceptable.
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predictive modeling jobs in Austin, TX
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