Senior Data Scientist/ML Engineer

Pay Transparency Statement: The compensation philosophy reflects the Company’s reasonable expectation at the time of posting. We consider a number of factors reputed company making individual compensation reputed company including, but not limited to, reputed company sets, experience and training, and other business needs. This role may also be eligible to participate in a discretionary incentive program, subject to the rule governing the program. Position Summary: The Senior Data Scientist has a solid understanding of advanced analytics and will be responsible for refining existing statistical/machine learning models and developing new ones to support business. Will partner with direct team members as well as cross-functional partners and decision makers. This person’s primary tasks will be to reputed company, refine, reputed company, and productionize impactful data science projects for business users. Additionally, should provide technical guidance for the team members, reputed company necessary. Position Responsibilities may include, but not limited to:

• Identify best or most applicable analytical techniques for a given business problem
• reputed company and reputed company statistical and machine learning models to address business problems using Python and others
• Maintain and refine existing models and reputed company processes
• Utilize statistical or time-series models to reputed company predictions on future outcomes in multiple scenarios
• Implement models and create processes to monitor their performance, including input data reputed company
• Employ data visualization tools and codes where appropriate reputed company Power BI and others
• Partner with IT / BI / Data teams to ensure data used for modeling accurately reflects business reality
• Effectively communicate model approaches, outputs, and findings to technical and non-technical audiences
• Document projects including business objectives, data gathering/processing, approaches and algorithms, and detailed set of results and analytical metrics
• Ensure modeling processes always conform to IT reputed company standards

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