Your new company
A series A tech start-up backed by top VCs including Sequoia and GFC.
Your new role
As a Lead/Chief Data Scientist (Fintech), you will be responsible for use of data and modelling to measure and limit our credit/fraud risk in B2B Payments and Credit, ensure high-quality decisions, and point towards new growth opportunities through the use of statistical, machine learning, algorithmic, and experimental techniques. You should be a self-starter who thrives on uncertainty and ambiguity, and be passionate about solving real problems with huge (and messy) or sparse (and limited) data sets.
This is an exciting zero-to-one role where you will lay the foundation as an individual contributor before subsequently building up a team.
- Partner with multiple team members to solve complex B2B payments and credit problems that extend beyond traditional or existing solutions by applying statistical, machine learning, and econometric models on large internal and external datasets
- Develop models and simulations to measure the full distribution of credit and fraud risk outcomes and detect potential risks
- Support the development of risk mitigation strategies and interventions while preserving and improving the user experience
- Shape and influence our data models and instrumentation to generate insights and develop new products, solutions, and models
- This is a technical business role (i.e. you should operate as a Data Strategist) which requires both the ability to analyse, model, and draw conclusions from data, as well as to critically evaluate, present, and discuss those conclusions with cross-functional stakeholders.
What you’ll need in order to succeed
The ideal candidate will possess a proven track record as a Lead-level data scientist coupled with subject matter expertise in the area of credit risk scoring & modelling. A huge plus if you come from embedded finance background and possess a strong understanding of the SME merchant market.
- At least 5-8 years of data science/quantitative modelling experience, including 3+ years’ experience in credit risk modelling or underwriting
- Strong understanding of financial industry models and experience building and calibrating those models to fit specific business needs
- Experience with machine learning pipelines, data visualization, data validation, statistical testing, and presenting findings to cross-functional audience
- Expert knowledge of a scientific computing language such as Python and SQL.
- Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners and high business impact
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner in excellent English since we're a regional team
What you’ll get in return
Besides enjoying an attractive salary package plus equities, you’ll get to work for a regional player with very strong global comparable.
What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV. If this job isn't quite right for you but you are looking for a new position within Data Science, please contact Daen Huang at +65 63030158
or email firstname.lastname@example.org for a confidential discussion on your career.
Hays Registration Number: 200609504D, EA License: 07C3924, Registration ID Number: R1658977