Data Science Manager

Department: Data Science

Location: Kuala Lumpur Office

Employment Type: FullTime

About Us

MoneyLion is America’s most powerful and rewarding financial membership, empowering people to take control of their finances to achieve their overall life goals.

Since its launch in 2013, MoneyLion has amassed more than 4 million members and has earned its customers trust with new banking and investments capabilities that offer a one-of-a-kind rewards program, no-fee checking account, overdraft protection, and loans funded in 15 seconds or less.

From a single application platform, users can get a holistic snapshot of their entire financial lives while having access to personalized and contextualized tips and tools to improve their credit and achieve everyday savings.

By rewarding financial responsibility, providing top-notch customer assistance and offering insightful financial education tips, we aim to positively impact our customers and enable them to better their financial health.

MoneyLion team members are passionate about making a difference in people’s lives. We work fast, collaborate always, and above all else, we do it for our customers.

About the Role

The Kuala Lumpur office is the technology powerhouse of MoneyLion. We pride ourselves on innovative initiatives and thrive in a fast paced and challenging environment. Join our multicultural team of visionaries and industry rebels in disrupting the traditional finance industry!

As a Data Science Manager in the Machine Learning Department, you will have the opportunity to lead a high-performing team responsible for developing the next generation of Moneylion’s machine learning algorithms behind MoneyLion’s data-driven products. You will lead research initiatives and experiment with state-of-the-art machine learning techniques to solve challenging business problems ranging from fraud and credit underwriting to financial recommendations and content categorization. This involves driving technological innovation across a large variety of domains while consistently delivering measurable business value and demonstrating accelerated team performance. You will extend your influence across Product, AI Engineers, MLOps, and Data Scientists to pioneer additional opportunities for applications of machine learning solutions. You will establish and enforce model governance standards across AI projects, provide confidence in the integrity of the models deployed, and push the frontier of machine learning in finance at MoneyLion.

Key Responsibilities

• Lead the technical direction and execution of the complete machine learning lifecycle, from research and development to validation, deployment, and post-production

• Envision and craft roadmap for machine learning projects towards well-defined success metrics

• Ensure the delivery of machine learning systems according to roadmap and with exceptional quality

• Provide thought leadership in ideating and innovating on cutting-edge techniques from literature to improve the performance of existing solutions

• Collaborate across company leadership and partner with stakeholders to drive adoption of machine learning models, identify and remove roadblocks while minimizing risk to the business and the team

• Define and drive best practices and model development policies to ensure the feasibility, generalizability, and stability of models while ensuring verbose documentation and diagrams are maintained

• Establish and define frameworks for ensuring robust development of machine learning codebase to enable maintainable and continuous improvements with measurable business impact

About You

• Demonstrated experience in leading data science teams with strong focus on success metrics

• Experience owning, building, and validating machine learning systems in production

• Practical experience with deep learning, computer vision, and NLP projects

• Proficient with machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, Keras

• Proficient in programming languages such as Python and SQL

• Strong understanding of data structures, data modeling and software architecture

• Deep knowledge of probability, statistics, distributions, and analysis methods

• Have strong product/business orientation

What's Next...

After you submit your application, you can expect the following steps in the recruitment process:

1. Online Technical Test

2. Interview - Talent Acquisition Team (Virtual or face-to-face)

3. Take-Home Assessment

4. Interview & Discussion of Take-Home Assessment - Hiring Manager (Virtual or face-to-face)

*If you’ve already sent in your application for this position and were not selected, please re-apply after 6 months.*