Information Technology - Data Sciences & Analytics Engineer (Data Science Track)
multiple positions for junior and senior data scientists to drive our AI, data
science and business analytics initiatives. Responsibilities include the
- 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.
- 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
- 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
- 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.