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Information Technology - Data Sciences & Analytics Engineer (Data Science Track)

Job Description

SIA has multiple positions for junior and senior data scientists to drive our AI, data science and business analytics initiatives. Responsibilities include the following:

  • Member of an in-house AI and data analytics development team that works on machine learning (including NLP, computer vision and recommender system using deep learning methods), mathematical optimization, game theory, and experimental design.
  • Work closely with business users to identify issues and use data to propose, build a scalable ML/DL solution and deploy as an API (primarily in Python) for effective decision making.
  • Oversee the technical work and provide datasets to external technology partners to deliver products/services in AI, data science and data analytics. Support business users in the assessment/validation of partner-supplied prediction models and in their deployment to production cloud.
  • Help business units create Tableau dashboards with relevant datasets. Extract insights through data visualization.
  • Work closely with application development teams to operationalize and integrate AI/machine learning/analytics capabilities into API microservices.

 

Requirements 

  • BS in Computer Science, Mathematics, Statistics, Physics or related discipline is required. PhD and master’s degrees related to computer science, machine learning and other AI disciplines are preferred.
  • Intermediate or advanced programming skills in Python. Conversant with algorithm design, data structure and SQL. Functional/object-oriented software development experience using modern programming languages such as Scala or Java is a big plus.
  • At least 2 years of relevant industry experience in two or more of the following areas:
    • Solid hands-on skills in shallow machine learning or information retrieval. Experience in GPU-accelerated deep learning frameworks (such as TensorFlow and PyTorch) is a plus for more advanced AI work.
    • Knowledge and working experience in workflow, map-reduce or stream processing systems such as Spark and Kafka.
    • Familiar with Bayesian statistics and inference. Exposure to the application of Bayesian and causal networks for probabilistic reasoning is a plus.
    • Knowledge and working experience with data visualization tools like Tableau or Power BI.
  • Experience with Agile/Scrum/Kanban methodologies is a plus.
  • Hands-on experience with AWS, GCP or similar public cloud environment.
  • Excellent interpersonal & communication skills to work with non-technical business users.
  • Proven ability as a problem-solver.