Senior Data Scientist

Posted 05 Feb 2019

eMoney Advisor


We are looking for a Senior Data Scientist to leverage machine learning across the entire eMoney technology portfolio. You will identify, prototype, and deliver high-impact data driven solutions for our products. You will work with our product and development teams to implement machine learning initiatives, setting data science standards and strategy. This role requires a breadth of technology and communication skills to influence and lead the strategic directions.

Job Responsibilities

  • Develop key Machine Learning solutions and own the execution pipeline; develop prototypes, implement production models, and work with Product, Ops, and App Development teams to ensure business value is fully realized
  • Develop core AI capabilities, e.g., MLAAS, data science architecture, to support machine learning and analytics use cases across all products
  • Help set AI and ML strategy across organization, identifying, prioritizing, and capturing high-impact business opportunities for Data Science and AI across entire eMoney portfolio
  • Explore new use cases and AI technologies for potential integration into eMoney
  • Ensure adoption of ML and Data Scientific approaches, providing guidance and internal consulting to software engineers, business owners, other data scientists

Requirements

  • 2 years working in a data science role
  • 4 years of software development experience
  • Master’s degree in related field or equivalent years of related experience
  • Experience with a variety of Data Science modeling use cases, including customer retention, marketing, digital analytics, segmentation, propensity modeling, etc.
  • Experience with data engineering, including consumption of data from relational and non-relational databases, flat files, etc.
  • Experience with integration with multiple internal and external systems
  • Experience in working in an agile environment to quickly iterate and deliver features to users
  • Experience in fintech strongly preferred

Skills

  • In depth knowledge of software development technologies and best practices for integration with data science: Python, Flask, Django
  • In depth knowledge of machine learning technologies: Spark, scikit-learn, deep learning frameworks (e.g., Tensorflow, PyTorch), computer vision, NLP (e.g., SpaCy, NLTK)
  • Strong written and verbal communication skills, ability to work with remote team members in virtual communication channels
  • Demonstrated ability to influence, communicate and lead technology and design decisions
  • Demonstrated abilities to communicate technology and product needs between product and engineering teams