Data Science Lead – Applied Innovation

Job description

The incumbent must come with strong financial and technical background, comfortable working with big data and building prototypes and MVPS across multiple levels of organization. 

One of the leading financial innovation lab is looking for an innovative professional who has strong financial background, machine learning and NLP technical skills.

Responsibilities:

• Build minimal viable products utilizing data science techniques directly for our customers
• Create compelling proposals with technologists and business to drive innovation from conception to production with appropriate success metrics
• Lead and inspire an extremely talented team of data scientists and sr. data scientists while actively contributing to projects and a manager
• Lead all projects from a data science perspective, removing obstacles and taking ownership to find creative solutions
• Manage senior level stakeholder engagements internally and externally to discover problems and use cases as well as to translate business impact of on-going and completed projects.
• Build domain expertise in financial market content and in Refinitiv data and products
• Network in the fintech, big tech and academic community through conferences, meetups and workshops – bringing leading edge techniques and technology into business strategy.

Requirements:

• 7+ years’ industry experience working in a data science role.
• Proven track record leading and contributing to data science teams, conveying objectives and expectations with clarity to align to business goals involving an inclusive, knowledge sharing and feedback oriented culture to nurture talent
• Experience producing and rapidly delivering minimum viable products, results focused with ability to prioritize the most impactful deliverables.
• Stellar interpersonal skills with a result-oriented attitude and a proven ability to handle multiple complex projects in a dynamic and collaborative group settings.
• High level of confidence in communicating with senior business and technical leaders internally and externally
• Experience working with large datasets to build unsupervised, semi-supervised and supervised for both machine learning and deep learning models
• Experience in at least several of the algorithm techniques.
• Ability to track down complex data quality and data integration issues, evaluate different algorithmic approaches, and analyze data to solve problems. Curiosity about the details of datasets is essential
• Domain knowledge in financial services such as quantitative finance, Financial Engineering, Electronic Trading or Risk Modelling.

Please contact Mabel Ngu at +65 6950 0366 or mabeln@charterhouse.com.sg for a confidential discussion

EA License no: 16S8066 | Registration no: R1980996

Only successful candidates will be notified.