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Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.
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Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, etc.) Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
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This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and cluster analysis.
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The incumbent will lead and help to develop a newly formed data-scientist team in delivering impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation.
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We're look for a Lead Data Scientist to spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives.
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Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). A master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 – 7 years’ experience in data science or a similar role.
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Foster a culture of innovation and continuous improvement and lead the exploration and adoption of new data science technologies and methodologies to contribute to the advancement of analytics' expertise.
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Provide input to the long/term plan for the Data Science team, including key focus areas, talent acquisition, input to technology platforms, and interaction model with the rest of the organization.
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Proficient in at least one analytical programming language relevant for data science. Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them.
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Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes. Manage use case design and build teams on day-to-day basis, providing guidance and feedback as they develop and operationalize data science models and algorithms to solve complex business problems.
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Keep abreast of the latest data science techniques and technologies. Explore and implement innovative solutions to improve data analysis, modeling capabilities, and business outcomes. Communicate complex data insights in a clear and effective manner to stakeholders across the organization, including non-technical audiences.
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Conduct ongoing research to stay abreast of the latest developments in machine learning, deep learning, and data science, and apply this knowledge to enhance project outcomes.
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Architecture Design: Design scalable and reliable data analytics and machine learning architectures leveraging the Databricks platform to meet business requirements and objectives.
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5+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
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machine learning jobs Title: data scientist Company: Verizon
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