MastercardSenior Data Scientist
Mastercard is hiring a Senior Data Scientist in Gurugram, India. Level rates it ; you can apply on Level.
AI in this role
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Data ScientistOur VisionAI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency.
Opportunity
Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate.
Role
• Develop AI/ML solutions/applications leveraging the latest industry and academic advancements.
• Strong theoretical understanding of statistical techniques, machine learning algorithms and their mathematical underpinnings.
• Interpret and explain model predictions and insights to varied audiences.
• Thrive in an unstructured environment, working autonomously on a strong team to find opportunity and deliver business impact.
• Leverage open and closed source technologies to solve business problems.
• Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda.
• Partner with technical teams to implement developed solutions/applications in production environment.
• Support a learning culture continuously advancing AI capabilities.
All About You:
Experience
• Demonstrated passion for AI competing in sponsored challenges such as Kaggle.
• Previous experience with or exposure to:
o Deep Learning algorithm techniques, open-source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL.
o Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning.
o Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil.
o Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks - Feedforward,
o CNN, LSTM's GRU's is a plus. Optimization techniques - Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets - Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing.
o Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus.
Effectiveness
• Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum.
• Capable of navigating a complex organization in a relentless pursuit of answers and clarity.
• Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness.
• Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation.
• Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment.
• Incredible attention to detail and focus instilling confidence without qualification in developed solutions.
Core Capabilities
• Strong written and oral communication skills
• Strong project management skill
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Abide by Mastercard’s security policies and practices;
Ensure the confidentiality and integrity of the information being accessed;
Report any suspected information security violation or breach, and
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
How we rate this
Senior Data Scientist at Mastercard rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $169k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used PyTorch in your day-to-day work.
- What are the limits of TensorFlow that you've run into, and how did you work around them?
- What's a project where you used Keras hands-on?
- Walk me through how you've used XGBoost in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: NLP, PyTorch, TensorFlow, Keras, and XGBoost. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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