Senior Data Scientist

Job Details

The Job Details Are As Follows As a Senior Data Scientist you will work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

Responsibilities

• Design, develop, and deploy advanced machine learning models and statistical algorithms to solve complex business problems and drive data-driven decision making across the organization
• Conduct rigorous statistical analysis, validate hypotheses, and provide actionable insights to stakeholders
• Build and optimize end-to-end data pipelines, including data extraction, transformation, and feature engineering to support scalable ML solutions
• Review, scale, and enhance operationalized statistical and machine learning models and algorithms, and quantify improvements in terms of business efficiency or customer experience
• Create repeatable processes and scalable data products by, for example, automating feedback loops for production statistical or machine learning models
• Implement MLOps best practices, including model versioning and monitoring to ensure reliable model performance in production
• Mentor junior data scientists and contribute to the development of team capabilities through code reviews, knowledge sharing, and best practice documentation
• Influence functional teams to develop best practices across the organization
• Identify areas of opportunity for data science to effect change and drive strategic business impact
• Maintain engagement with the data science community and current industry developments to assist in driving technical data science team vision and strategy

Requirements

• Master’s Degree in a quantitative field (Mathematics, Computer Science, or Statistics or related quantitative fields) and 5+ years professional experience in a data science role or PhD in a quantitative field and 2+ years professional experience in a data science, machine learning, or related analytical role
• Deep understanding of machine learning algorithms, statistical modeling techniques, and their practical applications, along with extensive experience using ML frameworks and libraries such as scikit-learn, TensorFlow, or similar tools
• Strong SQL skills and experience working with large-scale data warehousing platforms, particularly Snowflake
• Expert proficiency in a scripting language such as Python, including Python data libraries (numpy, pandas, matplotlib, scikit-learn) and strong programming skills in Java or similar languages
• Intermediate proficiency in a low-level or performant language
• Expert proficiency in working within a cloud computing environment using software development best practices
• Hands-on experience with cloud platforms (AWS and/or Azure) including services for data storage, processing, and model deployment
• Proven track record of deploying machine learning models to production environments and measuring their business impact
• Experience automating production-quality statistical or machine learning models at scale with expert understanding of their underlying mathematical and statistical theory
• Experience with version control (Git), containerization (Docker), and CI/CD practices
• Experience and expertise solving complex and highly impactful quantitative business problems
• Self-starting attitude; ability to spearhead new data science initiatives and collaboration across functional teams
• Demonstrates excellent communication skills with ability to explain statistic and mathematical concepts to non-experts