AVP, Machine Learning Engineer, Group Consumer Banking and Big Data Analytics Technology, Technology & Operations AVP, Machine Learning Engineer, Group Consumer  …

DBS Bank Limited
in Singapore
Permanent, Full time
Be the first to apply
Competitive
DBS Bank Limited
in Singapore
Permanent, Full time
Be the first to apply
Competitive
AVP, Machine Learning Engineer, Group Consumer Banking and Big Data Analytics Technology, Technology & Operations
Business Function
Group Technology and Operations (T&O) enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group T&O, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.
Roles & Responsibilities
  • Build and improve machine learning and analytics platform.
    • Apply cutting edge technologies and tool chain in big data and machine learning to build machine learning and analytics platform.
    • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
    • Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production.
    • Provide engineering solution and framework to support machine learning and data-driven business activities at large scale.
    • Verifying data quality, and/or ensuring it via data cleaning
    • Defining validation strategies
    • Defining the preprocessing or feature engineering to be done on a given dataset
    • Defining data augmentation pipelines
    • Training models and tuning their hyperparameters
    • Supervising the data acquisition process if more data is needed
    • Perform R&D on new technologies and solutions to improve accessibility, scalability, efficiency and us abilities of machine learning and analytics platform.
    • Deploying models to production
  • Work with data scientists to build end-to-end machine learning and analytics solution to solve business challenges.
    • Turn advanced machine learning models created by data scientists into end-to-end production grade system.
    • Build analytics platform components to support data collection, exploratory, and integration from various sources being data API, RDBMS, or big data platform.
    • Optimize efficiency of machine learning algorithm by applying state-of-the-art technologies, i.e. distributed computing, concurrent programming, or GPU parallel computing.
    • Support initiatives for data integrity and normalization
  • Establish, apply and maintain best practices and principles of machine learning engineering.
    • Study and evaluate the state of the art technologies, tools, and frameworks of machine learning engineering.
    • Contribute in creation of blueprint and reference architecture for various machine learning use cases.
    • Support the organization in transformation towards a data driven business culture.
    • Contributing to the overall solution design and architecture
  • Work Relationships
  • Internal
    • Work closely with data scientists, business team, and project managers to provide machine learning and data-driven business solution.
    • Collaborate with other technology teams to build platform and framework to enable machine learning and data analytics activities at large scale
    • Support overall project and team in the capacity of a ML Engineer.
    • Managing available resources such as hardware, data, and personnel so that deadlines are met
  • External
    • Maintain engineering principles and best practices of machine learning framework and technologies.
    • Document user requirements using Agile Frameworks
    • Working with Project Lead/Scrum Master to rapidly analyse data requirements and identify gaps.
    • Act as key conduit between development team and product owner.
Requirements:
  • At least 4 years+ of ML development or system design working experience
  • 2+ years of experience in machine learning system or data science research
  • Experienced as both a Data Scientist and Machine Learning Engineer
  • Experienced working in Software Engineering, DevOps and Data Engineering
  • Proficient in Python Data Science libraries such as but not limited to Numpy, Pandas, Numba & Scikit-learn.
  • Startup experience & Fintech Experience is a plus
  • Experienced/knowledgeable in A/B testing, uplift modelling for digital marketing. Reinforcement learning and Multi-Armed Bandits is a plus
  • Proficient in writing ETL using Airflow
  • Proficient in writing orchestration DAGs for Machine Learning Lifecycle Management
  • Proficient in creating dashboards with Streamlit & Grafana, Kibana is a plus
  • Experienced with ELK and logging with Python to ELK
  • Experienced in writing with Python: Flask, REST and GraphQL API endpoints or Middleware
  • Proficient in writing Multi-threading, Asynchronous and Multi-processing code in Python
  • Experienced with creating machine learning projects from start to finish from model creation to model deployment to production with proper CICD processes and Model observability and logging
  • Experienced in Image recognition for videos such as image annotation and OCR for PDF extraction tasks.
  • Experienced in MLOPS tools such as MLFlow for Machine learning cycle
  • Experienced in Data science enablement tools such as Kubeflow, with experience in Jupyter Notebooks and containerization of Machine learning models with serving tools such as KFServing and Seldon Core.
  • Proficient in writing Docker Files and creating Docker containers
  • Core professional expertise includes: Platform Architecture, Data Pipelines Architecture, Infrastructure Deployment and Management
  • Able to support existing and potential customers with requirements capture, solutions architecture, system design, solution prototyping
  • Experience in Kubeflow or Cloudera Data Science Workbench, is a big plus.
  • Experience with building traditional Cloud Data Warehouses, Data Lakes. Close and intensive work on previous projects with Containers and Resource Management systems: Docker, Kubernetes, Yarn.
Apply Now
We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.
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