Lead Data Scientist

4 weeks ago

Hong Kong, Hong Kong SAR China HSBC Full time

Some careers have more impact than others.

If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

Wealth and Personal Banking (WPB) helps deliver on HSBC’s purpose of opening up a world of opportunity by providing our customers with borderless banking and world-class wealth management through best-in-class, mobile-first capabilities and exceptional people. Our international network and breadth of expertise enable us to support individuals, families, business owners, investors and entrepreneurs. Wealth and Personal Banking has four key business areas responsible for efficiently bringing the best of HSBC to our clients through a broad and relevant suite of wealth and retail banking capabilities: Asset Management, Global Private Banking & Wealth, HSBC Life, Retail Banking & Strategy and COO & Digital Transformation.

We are currently seeking a high calibre professional to join our team as a Lead Data Scientist.

Principal Responsibilities

Work under Head of Data Science Solution as the leader role and ”go-to person” for business queries on analytical insights and machine learning Be responsible for managing the end-to-end business insights analytics and machine learning model lifecycle, starting from mining business opportunities based on analytic-driven insight mining, drafting business case and solution proposals, to leading the machine learning model experimental training, validation, finetuning and model governance documentation Own the technical solution design and implementation for the responsible AI / ethical bias testing with the lead of model governance in the team Work closely with business stakeholders to review the as-is business operation model and identify potential opportunities for optimization using Machine Learning or AI Requirements 5+ years of working experience in both hands-on machine learning model development and scaled enterprise analytics project management Proven programing skills for Machine Learning model training, evaluation, and fine tuning, in Python-based Machine Learning and Deep Learning framework Proficient in building quick prototype of Machine Learning based application with front-end and backend, in Python or Java Working experience in consulting firm serving enterprise client on AI & Machine Learning innovation initiative is preferred In-depth understanding and experienced in most commonly used Machine Learning algorithms and Data Science/Analytics methods Good understanding of DevOps, DataOps or MLOps Cloud-native data ETL development is preferred Technology stack provisioned in the team include: DataProc + Spark + Python on Google Cloud Airflow DAG for scheduling PyCharm / Visual Studio / IntelliJ as IDE for application development Jenkins / Terraform for deployment automation Java / Python packages and deep learning framework Multiple databases including PostgreSQL, BigQuery, graph databases, etc

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