Sr. Researcher (USA) - Research and Development

Data Science @ Tookitaki

The data science team is responsible for solving business problems on complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions and apply our analytical and machine learning skills to solve the problem in the best way possible. The problems that we tackle are focused on our 2 products/IP related to anti-money laundering (AML) and financial exception management. In addition, the team plays a pivotal role in shaping company IP, primarily in the area of approach, model selection, model tuning, and feature engineering, so that engineering can take this up and automate the same via a pipeline.

AMLS focus areas for the role

  • Name Screening 
    • Building an NLP pipeline to extract essential profile information from the free text;  
    • Finding the best solution to do entity resolution; 
  • Transaction Monitoring 
    • Upgrading the unsupervised pipeline to do more effective clustering and anomaly detection; 
    • Building a link analysis pipeline using graph databases and algorithms; 
    • Upgrading the supervised pipeline by improving on feature engineering and making clustering more effective 

The role has the following main responsibilities:

  • Identifying the key problems faced by our clients and the AML product, and executing a research plan to solve it; 
  • Implementing solutions to upgrade feature engineering and modeling pipelines of the AML product; 
  • Maintaining effective communication with the product, delivery, and engineering teams, and providing sufficient assistance based on priorities

Experience and Requirements

  • Ph.D. in relevant fields including computer science, physics, mathematics, etc.
  • Published paper in top ML/DL conference/journal is a plus 
  • Strong academic or work experience track record; Work experience in data science/machine learning from top companies or famous startups
  • Experience in fields that require extensive quantitative/coding, e.g. quant from hedge funds 
  • DS/ML competition experience like a top winner in Kaggle competition
  • Prior experience in Python and Spark; 
  • Ability to execute research plan using machine learning technologies; 
  • Excellent problem-solving skills; 
  • Expertise in NLP, graph database, and graph algorithms would be a plus.
  • Deep experience in big data would be a plus.

Desired Non-technical Requirements

  • Very strong communication skills both written and verbal
  • Strong desire to work with start-ups
  • Must be a team player

Job Perks

  • Attractive variable compensation package
  • Opportunity to work with an award-winning organization in the hottest space in tech – artificial intelligence and advanced machine learning