We are looking for a talented Principal Data Scientist to join with our Foundry Research and Development team to build innovative products delivered at scale to global markets.
Requirements
- Architects, designs and develops advanced machine learning models, predictive algorithms, and statistical solutions to solve complex business challenges, ensuring alignment with Mastercard’s strategic goals and technical standards.
- Communicates complex insights and data solutions effectively to both technical and non-technical stakeholders, including senior leadership, by drawing upon sophisticated data analysis, visualization, and feature engineering.
- Leads and influences high-priority data science initiatives, guiding teams on best practices regarding statistical hypothesis testing, data cleaning, and organization of large, complex datasets to uncover meaningful data patterns and trends.
- Innovates with complex data structures, modeling techniques, and parameter tuning to contribute to thought leadership initiatives by optimizing model performance, validating results with cross-validation and other metrics.
- Collaborates with senior AI/ML engineers and cross-functional teams to facilitate the scaling, deployment, and operationalization of models into production environments, ensuring adherence to technical best practices and quality standards.
- Contributes to Mastercard’s intellectual capital and capability development by recommending areas of opportunity for methodological innovation and process improvements.
- Mentors team members by sharing best practices, innovative techniques, and emerging trends to develop expertise and capabilities around their discipline.
- Expertise in architecting and creating production grade systems using various Machine Learning, Deep Learning and NLP concepts and models for both supervised and unsupervised learning.
- Proficiency with Python and related ecosystem of Data Science tools and packages including numpy, pandas, sklearn, spacy, keras, torch, transformers, langgraph.
- Sound Working Knowledge of optimization algorithms like Gradient Descent, its variants and related ecosystem of concepts like learning rates, batch sizes, loss functions and regularization strategies.
- Working knowledge of Python based API based frameworks like FastAPI and comfortable working with JSON objects.
- Good working knowledge of pyspark with conceptual understanding of parallel processing for huge data volumes.
- Expertise in applying various Statistical techniques and foundational concepts including different types of Hypothesis Testing.
- Expertise in creating solution architectures and pipelines.
- Experience in creation of Agentic AI applications using frameworks like langgraph and knowledge of Agentic AI design patterns and related concepts like Context Management, LLMOps, AgentOps, Guardrails, Agent Validation and Evaluation.
- Familiarity with Prompt engineering and working with both closed source models and open-source models.
- Working knowledge of MLOps tools like MLflow.
- Working Knowledge of LLM Finetuning is good to have.
- Strong hands-on experience in creating and executing optimized SQL queries and creating stored procedures with databases like Cosmos DB and Postgres DB.
- Experience in code configuration management with frameworks like github and bitbucket.
- Experience working with Unix commands for accessing various systems and databases and deploying and managing services / APIs.
- Working knowledge of cloud platforms like Azure and using Cloud Native services.
- Working knowledge of Databricks is good to have.
Benefits
- Competitive pay based on location, experience and other qualifications for the role
- May be eligible to participate in a discretionary annual incentive program
