AI/ML Data Scientist

The candidate should be comfortable collaborating with cross-functional teams, translating complex data science concepts into actionable business insights, and working in a fast-paced, agile environment.

• Design, develop, and implement AI/ML models to solve complex business problems using large and diverse datasets.

• Apply advanced data science techniques, including supervised and unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, and optimization.

• Develop reusable, maintainable, and scalable Python code libraries using functions, classes, and software engineering best practices.

• Build, deploy, and maintain production-ready AI/ML solutions using cloud platforms and high-performance computing environments.

• Implement and support AI/ML development pipelines, including CI/CD, workflow orchestration, and model deployment.

• Work with cloud technologies, distributed computing frameworks, and data platforms such as AWS, GCP, Azure, Databricks, Apache Spark, and Snowflake.

• Integrate enterprise-level APIs and work with relational and non-relational databases using SQL, NoSQL, and related technologies.

• Perform data analysis, visualization, and statistical modeling to generate meaningful business insights.

• Communicate complex technical concepts to non-technical stakeholders and translate business requirements into effective data science solutions.

• Collaborate with cross-functional teams in an agile environment, incorporating business feedback and adapting to evolving priorities.

• Follow version control, testing, documentation, and production software development best practices.

• Education and Experience:

  • PhD in Computer Science, Mathematics, Physics, Statistics, or a related quantitative discipline, with strong coding skills and at least 2 years of analytical experience; OR

  • Master's degree in a relevant discipline with at least 4 years of analytical experience.

• AI/ML Expertise:

  • Strong hands-on experience in AI/ML modeling involving complex datasets.

  • Solid understanding of AI/ML theoretical foundations and statistical methods.

  • Expertise in several areas, including supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, and optimization.

• Programming and Software Development:

  • Strong proficiency in Python for data science and AI/ML development.

  • Experience developing reusable code libraries, functions, and classes.

  • Experience building production-ready software and implementing CI/CD and orchestration workflows.

  • Familiarity with Git and other version control systems.

• Cloud and Data Technologies:

  • Experience with cloud platforms such as AWS, GCP, or Azure.

  • Familiarity with cloud-based AI solution development and high-performance computing environments.

  • Experience with Databricks, Apache Spark, and Snowflake.

  • Experience working with SQL, NoSQL, and other database systems.

  • Experience integrating and working with enterprise-level APIs.

• Data Visualization and Communication:

  • Knowledge of visualization and business intelligence tools such as Tableau, Power BI, and Plotly.

  • Strong business analysis, data storytelling, and analytical problem-solving skills.

  • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to business stakeholders.

• Experience in the life sciences or healthcare industry.

• Experience working within a large, complex, global organization.

• Proficiency in R and/or Scala.

• Familiarity with data science platforms and tools such as DataRobot, Dataiku, and Alteryx.

• Strong analytical and problem-solving abilities.

• Ability to collaborate effectively with cross-functional teams.

• Excellent stakeholder management and communication skills.

• Adaptability in a fast-paced, continuously evolving environment.

• Ability to manage multiple priorities while maintaining high-quality deliverables.

• Strong attention to detail and commitment to developing scalable, reliable AI/ML solutions.