Manager, Product Development & Innovation, AI (Neural Network, NLP, Chatbot development)
Job Description Summary :
Our Vision :
AI 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.
Lead a team of Data Science professionals in Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit within Mastercard, executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI.
- Be an AI subject matter expert at Mastercard, responsible for end-to end ownership and execution of assigned AI responsibilities.
- Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard.
- Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases.
- Gather relevant information to define the business problem interfacing with global stakeholders.
- Creative thinker capable of linking AI methodologies to identified business challenges.
- Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models.
- Develop AI/ML solutions/applications leveraging the latest industry and academic advancements.
- 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 :
- Prior experience leading and developing high performing teams with an emphasis on execution and through-put.
- Proven track record of developing and implementing AI strategies at scale, solving identified business problems and achieving optimization in the product development and management lifecycle in addition to operational efficiencies.
- Demonstrated leader capable of executing the AI agenda while managing complex variables including Information and Data Governance, Data Management, Information Security, Privacy & Compliance, Content Life cycle Management, and Records Retention Demonstrated ability to deliver high quality AI solutions in a matrix organization, thinking out of the box and solving hard problems while navigating through ambiguity.
- 8+ years of experience in the Data Sciences field with a focus on AI strategy and execution, developing solutions from scratch and building local and global teams.
- Demonstrated expertise in the Data Sciences with established credibility in the field including patent submissions and experience working with start-ups.
- Demonstrated passion for AI competing in sponsored challenges such as Kaggle.
Previous experience with or exposure to :
- Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL.
- Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning.
- 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.
- Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks - Feedforward, 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.
- 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.
Exposure or experience using collaboration tools such as :
- Confluence (Documentation).
- Bitbucket/Stash (Code Sharing).
- Shared Folders (File Sharing).
- ALM (Project Management).
- Knowledge of the payments industry a plus.
- Experience with SAFe (Scaled Agile Framework) process is a plus.
- 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 enabling the identification, design, and deployment of optimal AI and machine learning business opportunities and the creative application of AI techniques to improve an organization's effectiveness.
- Proven thought-leadership when evaluating business problems and architecting a cohesive solution.
- 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 skills.
- Experience leading teams a plus.
- Bachelor's degree required. Advanced degree in Management, Mathematics, Computer Science, Engineering, or other quantitative fields desirable.
- Some international travel required.