Senior Data Scientist ( Onsite)

Job summary

Job Summary: Drive end to end design and implementation of advanced data science solutions that leverage Azure Open AI Service and Python to solve complex business problems and deliver measurable improvements in operational efficiency and customer experience across multiple business units Responsibilities : - Oversee development of robust machine learning and artificial intelligence models includi

Benefits

Qualifications

• privacy standards and security controls especially for sensitive data in retail customer services and utilities contexts where trust and reliability are critical -
• Please note this role is not able to offer visa transfer or sponsorship now or in the future*
• We're excited to meet people who share our mission and who can make an impact in a variety of ways.
• Don't hesitate to apply—even if you only meet the minimum
• Think about your transferable experiences and unique
• of the successful candidate.
• This position is also eligible for Cog***’s discretionary annual incentive program, based on performance and subject to the terms of Cog***’s applicable plans.
• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave

Responsibilities

• Mentor and guide data science team members by reviewing solution designs code quality and analytical approaches to ensure consistent use of best practices and scalable patterns across projects
• Drive optimization of Python based pipelines and model deployment workflows by improving code modularity performance and reliability while promoting modern development practices and efficient use of cloud resources
• Analyze large and complex structured and unstructured datasets to uncover actionable insights that inform pricing strategies service optimization personalized experiences and long term planning for enterprise clients
• Coordinate evaluation of new Azure Open AI capabilities and artificial intelligence frameworks and plan incremental adoption that reduces risk while improving innovation speed and solution quality
• Drive continuous improvement of data science methodologies by analyzing project retrospectives identifying process gaps and implementing enhancements that increase delivery predictability and stakeholder satisfaction
• Ensure that all data science solutions comply with regulatory

Skills

Degrees

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