Manager, Data Scientist

• Responsible for developing data-driven innovative scalable analytical solutions and identifying opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations / decisions.
• Accountable for delivering high quality project solutions and tools within agreed upon timelines and budget parameters and conducting post- implementation reviews.
• Contributes to the development of custom analyses and solutions, derives insights from extracted data to solve critical business questions.
• Activities include developing and creating predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations.
• Able to develop AI/ML capabilities, as needed on large volumes of data to support analytics and reporting needs across products, markets and services.
• Able to build end to end reusable, multi-purpose AI models to drive automated insights and recommendations.
• Leverage open and closed source technologies to solve business problems.
• Work closely with global & regional teams to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support analytics and reporting needs across products, markets, and services. Support initiatives in developing predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations.
• Translates client/ stakeholder needs into technical analyses and/or custom solutions in collaboration with internal and external partners, derive insights and present findings and outcomes to clients/stakeholders to solve critical business questions.
• Serve as a primary point of contact for client managers and liaises frequently with internal Product Managers, Account Managers, Engineers to gather data or inputs needed for project work.
• Delegate and reviews work for junior level colleagues to ensure downstream applications and tools are not compromised or delayed.
• Serves as a mentor for junior-level colleagues, and develops talent via ongoing technical training, peer review etc

• 10+ years of experience in data management, data mining, data analytics, data reporting, data product development and quantitative analysis.
• Advanced SQL skills, ability to write optimized queries for large data sets.
• Experience on Platforms/Environments: Cloudera Hadoop, Big data technology stack, SQL Server, Microsoft BI Stack, Cloud, Snowflake, and other relevant technologies.
• Experience on Deep Learning algorithm techniques, open-source tools and technologies, statistical tools, and programming environments such as Python, R, and Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning.
• Experience on Classical and Deep Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks - Feedforward, CNN, NLP, etc
• Experience in automating and creating data pipeline via tools such as Alteryx, SSIS. Nifi is a plus
• Data visualization tools (Tableau, Domo, and/or Power BI/similar tools) experience is a plus
• Experience with data validation, quality control and cleansing processes to new and existing data sources.
• Financial Institution or a Payments experience a plus

Additional Competencies

• Excellent English, quantitative, technical, and communication (oral/written) skills.
• Ownership of end-to-end Project Delivery/Risk Mitigation
• Virtual team management and manage stakeholders by influence
• Analytical/Problem Solving
• Able to prioritize and perform multiple tasks simultaneously
• Able to work across varying time zone.
• Strong attention to detail and quality
• Creativity/Innovation
• Self-motivated, operates with a sense of urgency.
• In depth technical knowledge, drive, and ability to learn new technologies.
• Must be able to interact with management, internal stakeholders