Senior Data Scientist

Our client is one of the fastest-growing digital players in its field. They're expanding in APAC, and looking for a Senior Data Scientist to join their exciting journey.

Responsibilities

We are looking for a data scientist with a risk management background who is familiar with a broad spectrum of modeling techniques (both classical ML and various deep learning modeling approaches) utilizing a wide variety of data types (e.g. transactional financial data, system log data, clickstream data, geospatial data, customer support chat log, audio recordings, image, and video data, etc) to be able to build models using both traditional and alternative data sources in support of the credit risk team, e.g. probability of default, loss given default, expected profitability, application score cards, behavior score cards, etc. On top of model design and development, key responsibilities of the role include model deployment, operationalization, monitoring, and maintenance. The machine learning platform team will provide close support in these areas. Strong communication skills are essential to help communicate complex ideas to less technical audiences. Experience with complex financial modeling is highly desirable as is a background in risk management.

Qualifications

• A Master’s Degree or Ph.D. in Computer Science, Statistics, Physics, Mathematics, or other related degrees. Candidates from a background in finance and economics who have moved into data science will also be considered as long as they also have strong statistical and mathematical knowledge

• A financial risk management certification or professional qualification (e.g. actuary, FRM, etc) would be highly valued

• Experience with developing and/or validating IFRS9 or Basel II models is a plus

• Understanding of the theoretical foundations underpinning machine learning and deep learning models while also having hands-on experience dealing with the problems they throw up in the real world

• 1+ years of experience in deploying machine learning models in production environments

• 3+ years of experience in building machine learning and deep learning models

• Strong familiarity with tools within the PyData ecosystem such as Numpy, Scipy, Pandas, Scikit-Learn, PyTorch, TensorFlow, SpaCy, etc.

If interested, please apply! Please note that due to high application volumes, we regret that only successful candidates will be contacted.

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