Senior data scientist - Applied AI

Reporting to the Manager of Applied AI and working with the Mastercard Applied AI Technology team, the Senior Data Scientist will drive enterprise-level impact from data science solutions by defining technical approaches to business problems, rapidly prototyping and developing models, and working with ML Engineers to bring models up to full production scale.

The Role

1/ Define technical approaches to business problems

• Work with AI strategy managers to define high-level business and technical designs for data science and analytics solutions

• Co-create and validate solution designs with data science colleagues

• Propose logical versioning strategies to iteratively build solutions from PoC to mature end state

2/ Rapidly prototype and develop models

• Research cutting edge approaches and design and execute small PoCs to select the optimal approach.

• Iteratively develop models with frequent feedback from business partners and technical leaders

• Design and assist in the development of end-to-end model pipelines, from data aggregation and cleaning to model validation and visualization

3/ Bring models up to full production scale

• Assist ML engineers in designing applications to run your models at scale

• Develop drift monitoring strategies and tests to ensure your models are performing in live production settings

• Deploy frequent updates to live models to constantly increase business impact

All about you

• 4+ years of industry experience in data science

• Strong experience in Python

• Extensive expertise in statistical modeling, machine learning algorithms, and predictive analytics.

• Highly structured and organized work planning skills

• Strong understanding of the AI development lifecycle

• Proficiency in big data technologies like Hadoop, Spark, or similar frameworks. Experience with graph databases a plus.

• Excellent skills in data visualization and interpretation using tools such as Tableau, Jupyter, RShiny, etc

• Demonstrated history of successfully delivering high-quality, data-driven solutions, including deploying production-level machine learning models and executing complex business intelligence projects.

• Excellent communication skills, capable of explaining complex data concepts in simple terms.

• Experience in working with cloud computing platforms like AWS, Azure, or Google Cloud.

• Proven track record of delivering data products in environments with strict adherence to security and model governance standards.

• Bachelor's degree in computer science, analytics, mathematics, statistics, economics, industrial engineering, or physical sciences. Master’s degree in one of these disciplines preferred.