Senior Information Strategist

Job Title: Senior Data Scientist

We are seeking a highly skilled professional to support the development of AI tools for customers.

The ideal candidate will have expertise in using large datasets to identify opportunities for product and process optimization.

Key Responsibilities:

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• Collaborate with stakeholders to leverage data for business solutions\
• Analyze data from databases to drive optimization and improvement of product development and business strategies\
• Assess the effectiveness and accuracy of new data sources and data gathering techniques\
• Develop custom models and algorithms to apply to data sets\
• Design and implement advanced statistical models and machine learning algorithms to improve data-driven decision making\
• Work closely with cross-functional teams to integrate data science into business operations\
• Stay up-to-date with emerging trends and technologies in data science and AI\
• Contribute to the development of predictive models and data visualizations to inform business strategy\
• Develop and maintain complex data pipelines and systems to support data analysis and modeling\
• Collaborate with data engineers to design and implement scalable data architectures\
• Communicate complex technical ideas to both technical and non-technical stakeholders\
• Provide expert advice on data science methodologies and tools to stakeholders\
• Stay current with industry trends and developments in data science and AI\
• Conduct thorough literature reviews and stay up-to-date with the latest research in data science and AI\
• Develop and maintain documentation of data science processes and procedures\
• Lead or participate in projects that involve data analysis, visualization, and modeling\
• Collaborate with other departments to ensure seamless integration of data science into business operations\
• Identify areas for process improvements and develop recommendations for implementation\
• Develop and maintain relationships with key stakeholders, including business leaders, product managers, and engineers\
• Communicate the value and impact of data science to stakeholders\
• Provide training and mentorship to junior team members\
• Conduct code reviews and provide feedback to team members\
• Participate in hackathons and other innovation initiatives to stay creative and innovative\
• Collaborate with external partners and vendors to access new technologies and expertise\
• Develop and maintain knowledge of industry-leading tools and platforms in data science and AI\
• Stay current with industry certifications and compliance requirements related to data science and AI\
• Ensure adherence to company policies and procedures related to data governance and security\
• Identify and mitigate risks associated with data science projects\
• Document and communicate lessons learned from project experiences\
• Develop and maintain skills in relevant programming languages, such as R, Python, and SQL\
• Stay current with advancements in machine learning and deep learning\
• Develop and maintain expertise in cloud-based data science platforms, such as Azure Machine Learning\
• Collaborate with data architects to design and implement data warehouses and data lakes\
• Develop and maintain knowledge of data management best practices\
• Stay current with industry trends and developments in data governance and compliance\
• Ensure adherence to regulatory requirements and industry standards related to data privacy and security\
• Develop and maintain relationships with key stakeholders, including business leaders, product managers, and engineers\
• Collaborate with other departments to ensure seamless integration of data science into business operations\
• Identify areas for process improvements and develop recommendations for implementation\
• Develop and maintain documentation of data science processes and procedures\
• Communicate the value and impact of data science to stakeholders\
• Provide training and mentorship to junior team members\
• Conduct code reviews and provide feedback to team members\
• Participate in hackathons and other innovation initiatives to stay creative and innovative\
• Collaborate with external partners and vendors to access new technologies and expertise\
• Develop and maintain knowledge of industry-leading tools and platforms in data science and AI\
• Stay current with industry certifications and compliance requirements related to data science and AI\
• Ensure adherence to company policies and procedures related to data governance and security\
• Identify and mitigate risks associated with data science projects\
• Document and communicate lessons learned from project experiences\
• Develop and maintain skills in relevant programming languages, such as R, Python, and SQL\
• Stay current with advancements in machine learning and deep learning\
• Develop and maintain expertise in cloud-based data science platforms, such as Azure Machine Learning\
• Collaborate with data architects to design and implement data warehouses and data lakes\
• Develop and maintain knowledge of data management best practices\
• Stay current with industry trends and developments in data governance and compliance\
• Ensure adherence to regulatory requirements and industry standards related to data privacy and security],