SMBC Group

Senior Data Scientist & Machine Learning Engineer (Innovation & Fintech)

Job Locations US-NY-New York
Posting Date 2 months ago(5/17/2021 3:12 PM)
Career Category
Corporate Title


Reporting to the Head of Innovation Technology, the Senior Data Science / Machine Learning Engineer performs statistical analysis and data science work in support of the Innovation and Fintech team’s goals and objectives and will evaluate methodologies and analyses for statistical rigor. The candidate should be equipped and ready to serve as a leader to data scientists and data engineers across the Americas Division of SMBC while also keeping abreast of the latest techniques and trends that may benefit the achievement of the Team's objectives.


This Senior Data Science/ Machine learning Engineer will perform and oversee the delivery of ML models and components, joining various data sources to solve complex business problems. They will also be responsible for testing, tuning, and optimization work associated with Innovation and Fintech Team projects and initiatives.


  • Establish Data Science capabilities to support the creation of Machine Learning products and capabilities across the SMBC Group in the Americas
  • Work with Innovation Team members to build a backlog of Machine Learning prototypes and experiments to help reduce costs, grow revenue, or decrease risk. 
  • Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Innovation, Business and Technology teams.
  • Identify, source, transform and join public, proprietary and internal data sources.  Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications.
  • Coach and develop data scientists and data engineers across SMBC Group.
  • Work as a data Scientist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products; leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
  • Experience with programming environments (Jupyter, Google Collab) and machine learning toolkits (Scikit Learn, Tensor Flow, Keras,  etc.) and Data Science packages (e.g., DataRobot)
    Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Code deliverables in tandem with the engineering team.
  • Develop knowledge of new analytical techniques and data sources that provide ongoing risk mitigation, and how emerging data and technology issues may impact the achievement of Innovation and Fintech Team objectives.


  • Master degree (or equivalent practical experience) in Statistics, Computer Science, Engineering, or Mathematics, or related quantitative discipline -- PhD a plus.
  • 4+ years of professional software development and/or statistical/mathematical or data science experience.
  • 3+ years of programming experience with at least one modern language such as Java, C++, or C# including object-oriented design.
  • Extensive statistical experience, including model development and evaluation, experimentation and inference. (specific areas of highly relevant experience include causal inference, forecasting, operations research and optimization)
  • Strong Python and SQL background.
  • Experience implementing models and understanding of CS fundamentals (data structures, algorithms), and how software scales.
  • Experience developing data pipelines: data warehouse management, ETL and development of scalable analytics schemas.
  • Experience with Excel, PowerPoint, Tableau, SQL, and programming languages. (i.e., Java/Python, SAS)
  • Experience with Google Collab, Tensor Flow, Keras, Scikit Learn, etc.
  • Technical competence to perform advanced analytics: coding skills (such as R, Python, or Scala), experience with analytics and visualization tools. ( SQL, Tableau, ggplot/matplotlib or equivalent)
  • Experience working with out of the box data science tools including UIPath, DataRobot, etc. is a plus.



Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed