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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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Key Responsibilities: Lead the engineering team in designing, developing, and deploying solutions applying modern web frameworks, machine learning solutions, data engineering technologies, microservices, and cloud-native architecture.
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Expertise in data strategy, data architecture, data engineering, advanced analytics, data science, data mining, and machine learning. Has experience managing on-shore and off-shore teams and knows how to optimize operating models to ensure data entry, data operations, and data thought leadership is being performed by the right talent base with scale and speed.
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Leading: Mentor and guide junior engineers, fostering a culture of continuous learning and professional growthTHE ESSENTIALS FOR SUCCESS: BS or MS degree in Computer Science, Artificial Intelligence, Machine Learning, or other related degrees (e.g., Applied Mathematics) with a focus on Machine Learning.
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Understanding or hands on experience with Lex, Nuance Mix, Dialog Flow, AWS and Google Cloud, R, Power BI, Tableau, Alteryx; Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms.
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We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology.
$232,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value.
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Managing daily operations of a global data and analytics team on client engagements, review developed models, provide feedback and assist in analysis; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
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Understanding of data privacy and security regulations and best practices; As part of our Analytics and Insights Consumption team, you'll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes.
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Managing a team of AI consultants, data scientists, developers and designers, providing guidance, support, and mentoring to ensure the team is aligned with the company's strategic goals; A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics.
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Develop a point of view on key global trends, and how they impact clients. Use data and insights to inform conclusions and support decision-making. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage.
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Using Python (e.g., Pandas, NLTK, etc.) It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.
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Understanding or experience with Contact Center as a service providers such as Nice, Nuance or Genesys and leading contact center transformation projects. Using chatbot development frameworks, such as RASA or Microsoft Bot Framework.
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Data, Analytics & AI. Applying experience with cloud platforms, such as AWS, Google Cloud, or Microsoft Azure; Understanding or experience with conversational AI platforms, such as Google Dialogflow, Amazon Lex, IBM Watson, Microsoft Azure hyper-scalers.
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machine learning data mining hands on r python jobs Company: Techdata Service Company Llc
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