Assistant Manager / Manager, Data Scientist

Welab Bank Limited; Hong Kong; On-site; HKD 480,000 - 900,000; Full time

Benefits offered by this job

Learning and development stipend

Wellness and flexible time off

Open plan office with free food

Job summary

WeLab seeks an Assistant Manager / Manager, Data Scientist to design and deploy predictive models and pricing solutions for banking products. You will analyze large datasets to uncover features that improve business outcomes and contribute to MLOps practices including model versioning and monitoring.

The role involves collaborating with product, risk, and marketing teams, building dashboards, and delivering data-driven insights.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or another quantitative field
• 3–5 years hands-on Data Science/ML experience
• Experience or interest in banking/fintech is a plus, esp. credit scoring, fraud, pricing, customer analytics
• Strong proficiency in Python and SQL with ML frameworks
• Experience with Spark/PySpark or big data tech
• Familiarity with cloud ML platforms (AWS SageMaker/Vertex AI) and MLOps tools (MLflow, Git)
• Able to translate business needs into data-driven solutions

Responsibilities

• Design, develop, and enhance predictive models, pricing, recommendations, and automation tools
• Perform deep-dive analyses on large datasets to improve model performance and outcomes
• Support deployment of ML models into production and MLOps practices
• Explore Generative AI and NLP solutions including LLMs and sentiment analysis
• Feature engineering, hyperparameter tuning, model validation, bias assessment
• Collaborate with Product, Marketing, Risk to translate needs into solutions
• Develop dashboards to communicate results to stakeholders

Skills

Python

SQL

Machine Learning

Big Data

Spark/PySpark

Cloud ML

MLflow

Git

Education

Bachelor's degree in CS/DS/Statistics/Math

Master's degree in Data Science

Tools

AWS SageMaker

Google Vertex AI

TensorFlow

PyTorch

Scikit-learn

Spark

Job description

Assistant Manager / Manager, Data Scientist

WeLab, a leading pan-Asian fintech platform, operates two digital banks (WeLab Bank and Bank Saqu) as well as multiple online financial services in Hong Kong, Mainland China and Indonesia, with over 70 million individual users and over 700 enterprise customers. WeLab uses game-changing technology to help users access credit, save money, and enjoy their financial journey.

AtWeLab, we always put our people first. Embarking on a career withWeLabmeans being part of the driving force to make financial services accessible for everyone. In our flat and agile organization, you will get all the opportunities to make real impacts and deliver change. Most importantly, while you achieve greatness, we will ensure you have an amazing experience atWeLab!

Our team is energetic and passionate who can deliver and execute, and we are looking for intellectually curious, open-minded, and smart-working individuals who are just as passionate as we are about making financial services enjoyable.

Join us to build a better financial future for everyone!

About You:

You're a go-getter with mad juggling skills (or multiple hats) who can thrive in a fast-paced, agile environment

You enjoy doing purpose-led and meaningful work

You have a strong thirst for knowledge and are driven to find solutions that don't exist yet

You are comfortable with ambiguity and extremely resourceful (in your past life, you could've been a detective)

You always find a way to get things done without sacrificing the quality of your work, integrity, and values

No task is off limits for you

You are humble and prioritize the success of the team over your own with an eagerness to help those around you

You don't shy away from challenges and can bounce back from setbacks

What you’ll do and what success looks like:

Design, develop, and enhance predictive models, pricing solutions, recommendation engines, and automation tools to support a range of banking products and services

Perform deep-dive analysis on large and complex datasets to identify trends, patterns, and key features that improve model performance and business outcomes

Support the deployment of machine learning models into production and contribute to MLOps practices, including model versioning, monitoring, and ongoing performance management

Explore and implement Generative AI and NLP solutions, including Large Language Models (LLMs), sentiment analysis, and automated document processing

Conduct feature engineering, hyperparameter tuning, model validation, and bias assessment to enhance model accuracy, robustness, and fairness

Partner closely with Product, Marketing, Risk, and other business teams to translate business needs into practical, data-driven solutions

Develop dashboards and visualizations to communicate model performance, analytical findings, and actionable insights to stakeholders

What we’re looking for:

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or another relevant quantitative discipline

3 to 5 years of hands-on experience in Data Science, Machine Learning, or a related analytical role

Prior experience or strong interest in banking or fintech is an advantage, particularly in areas such as credit scoring, fraud detection, pricing, customer analytics, or customer lifetime value

Strong proficiency inPython and SQL, with hands-on experience using machine learning frameworks and libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch

Practical experience withSpark/PySpark or other big data technologies for processing and analyzing large-scale datasets

Familiarity with cloud-based machine learning platforms such as AWS SageMaker or Google Cloud Vertex AI, together with exposure to MLOps tools and practices such as MLflow and Git

Strong analytical and problem-solving skills, with the ability to work through ambiguity and translate complex data into practical solutions.

Candidates with less experience may be considered for the Assistant Manager level

Will be great if you have:

Experience in digital banking, virtual banking or fintech environments.

Experience leading workflow automation, digital transformation or operational excellence initiatives.

Experience managing system enhancement projects and UAT activities.

Familiarity with capacity planning, productivity management and workforce optimization.

Experience managing cross-border teams will be an advantage.

Experience using AI-powered productivity tools, workflow automation platforms, data analytics solutions or emerging technologies to improve operational performance.

Demonstrated ability to leverage technology and innovation to drive operational transformation and customer experience enhancement.

Perks and Benefits to enrich your experience at WeLab:

Learning and development stipend - we value lifelong learning and believe the best way to invest in our employees is to encourage them to continue to learn

Wellness and happiness – Numerous activities to let you focus on your physical and mental wellbeing. We allow flexible time offs to take care of personal matters and to enjoy time with family and friends

Comfortable and positive work environment – Open plan office for easy collaboration and social with your colleagues, or branch out into your own thinking pods when needed, with FREE food and drinks for when you want to recharge

Work smart, play hard – Connect with your colleagues over food and drinks at the stocked pantry, in the spacious social area with board games and a ping pong table, or over activities like hiking, yoga, badminton, etc.

A big and contagious smile on everyone’s face to make you happier :)

Asia Banking FinanceRetail Banking Awards:Virtual Bank of theYear-Hong Kong

CNBC Disruptor 50:the only Hong Kong-based company on the list

Financial TimesAsia-Pacific High-Growth Companies:#2in ranking

The Chinese University of Hong Kong“Corporate Innovation Index”:#1inranking

We offer a competitive salary package to the successful candidate.

All information provided by applicants will be used for recruitment purposes only. Information of unsuccessful applicants will be destroyed within 24 months of receipt.