Data Scientist

Required Education and Experience

• Master’s degree in Computer Science, Mathematics, Statistics (Theoretical/Computational), Data Analytics, Data Science, Machine Learning, or Artificial Intelligence
• 5+ years of experience in a data-driven organization with a strong technical focus

General Requirements

• Strong technical competency and programming skills in Python, R, and awareness of other relevant languages (Spark, Pandas, T-SQL, PL-SQL)
• Proficient in analyzing, designing, developing, testing, troubleshooting, and documenting complex systems, including predictive and prescriptive models, feature extraction, and machine learning algorithms
• Expertise in data migration, integration across datasets, cloud tools usage, and technology platforms, with a focus on Machine Learning in the Azure cloud
• Deep analytical capability for debugging, monitoring, and troubleshooting data solutions
• Effective communication and leadership skills to influence data-driven decision-making at various organizational levels
• Ability to translate technical jargon into meaningful business insights
• Strong consulting skills with a track record of working collaboratively and influencing others
• Continuous self-learner with a keen understanding of industry trends in the data space
• Effective multitasking, handling multiple assignments, and conflicting priorities
• Innovative and results-oriented
• Strategic thinker with an enterprise view for sustainable solutions
• Committed to continuous learning and improvement
• Committed to the development of others
• Committed to building and maintaining constructive partnerships with business partners
• Works well both independently and with others
• Acts with speed and decisiveness
• Committed to ethical conduct
• Lives and works safely

Preferred Requirements

• Experience around Generative AI and/or LLM would be a plus

Essential Functions

• Analyze data to identify and develop AI/Machine Learning use cases aligned with business objectives
• Stay current on emerging AI/Machine Learning technologies, educating the team on their applications and optimal leverage
• Devise innovative algorithmic approaches to address complex quantitative problems using large-scale enterprise data
• Train, validate, and optimize machine learning models for various use case needs
• Adopt new tools and algorithms effectively to enhance model performance
• Develop and implement an AMI AI development framework within the AMI Governance Committee, emphasizing MLOPS practices for seamless model deployment to the cloud
• Provide training on the framework, enabling effective change management to monitor and enhance model performance
• Collaborate with cross-functional teams to provision ETL processes and establish CI/CD pipelines for continuous model deployment and updates
• Complete comprehensive documentation and statistical system documentation to communicate results effectively
• Collaborate with end-users to identify data management and analytical solution needs, fostering improved data-driven decision-making
• Mentor team members to enhance their skills and abilities
• Perform other tasks as required