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Manpower Staffing Services
Manpower Staffing Services Singapore Singapore
2 weeks ago
Responsibilities:
• Involve in deploying machine learning models, data science solutions and working with state-of-art data science and machine learning tools such as Spark, Sklearn, Tensorflow and will have proficiency in any number of analytic programming /platforms like Python, R. etc.
• Work with large datasets, distributed Big Data Platforms, CI/CD tools for continuously deploying variety of advanced analytics solutions across the bank ranging from recommendation engines, propensity models, customer segmentation, graph models, credit underwriting model, pricing and more
• Engage with data science/machine learning project teams, business, and product teams to create the deployment framework
• End-to-End processes for feature engineering, model deployment and model performance monitoring
• Deploy A/B test experiments to test the model effectiveness and analyze to identify the target segments
• Drive the Big data infrastructure/ Data engineering team to set up the production... environment
• Build reusable, scalable deployment frameworks
Requirements:
• B.Sc./M.Sc./PhD or equivalent degree in Statistics, Analytics, Applied Mathematics, Operation Research, or equivalent quantitative fields
• 3+ years of experience with machine learning or other advanced analytics topics such as Bayesian inference, graph theory or optimization
• 3+ years of experience with data exploration and interpretation, including feature selection and creation, AB testing, statistical hypothesis testing and/or data visualisation
• 3+ years of experience with manipulation of relational data (for example SQL tables or Data frames)
• Experience with production-grade data science and software development practices such as Agile development, code versioning, unit testing, continuous integration and deployment, data and model monitoring, bias analysis, etc.
• Excellent programming skills in either Python, R, Java, or Scala
• Experience with building and deploying ETL pipelines, or deploying applications in shared environments using Yarn, Airflow and Kubernetes
Singapore
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