Sr Risk Data Scientist

Sr Risk Data Scientist

This position offers you the opportunity to join a fast-growing technology organization that is redefining productivity paradigms in the software engineering industry. If you are passionate about technology and want to learn about new trends that are shaping human behavior, this opportunity is for you.

The Risk Data Science team is looking for a Data Scientist to develop advanced machine learning models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas. The Data Scientist will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions to enhance the loan origination process, improve fraud detection and prevention, and support loss mitigation, etc. These tasks involve developing complex business rules to researching and applying state of the art machine learning modeling methodologies to solve complex business problems. This role is very rewarding as your work will have a direct and immediate impact on the business’ profitability.

The impact you'll make:

• Develop, implement and continuously improve machine learning models and strategies that support various credit and operational procedures including but not limited to underwriting, account and/or portfolio management, loan processing enhancement, fraud detection and prevention, and loss mitigation etc...
• Proactively identify opportunities to apply advanced machine learning approaches (e.g., supervised and unsupervised learning algorithms, graph database and graph modeling, GenAI, NLP, Image Recognition, etc...) to solve complex business problems.
• Explore an leverage in-house, external, and other open-source machine learning software/algorithms
• Collaborate with the Model Risk Management team to demonstrate models are developed with high level rigor that satisfy Model Risk Management and Governance requirements.
• Work closely with the Product and Engineering teams for model deployment.
• Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking
• Present model performance and insights to Credit, Risk, and Business Unit leaders.

Technology stack:

• Programming Languages: Python, java, R, SQL, R, Excel
• Frameworks: Jupyter, AWS, Spark/Hadoop, Tableau, TensorFlow, Scikit-learn, Seaborn, Matplotlib, NumPy, Snowflake, Pandas, Postman.
• Microservices: Consume Services only.
• Databases: MongoDB, Snowflake, Posgresql.
• Cloud: AWS, Snowflake

What you'll bring to us:

• Bachelor's degree in Computer Science, Statics, Mathematics, Physics, Engineering, or quantitative field required. Master's or higher degrees preferred.
• 6+ years of experience building statistical or machine learning algorithms in a commercial setting and deploying these in production. These methods include, regression, clustering, outlier detection, novelty detection, decision trees, nearest neighbors, support vector machines, ensemble methods and boosting, neural networks, deep learning and its various applications, GenAI and its applications.
• Continuously follow the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies.
• Experience in working closely with Product, Engineering and Model Risk Management teams.
• Solid experience in Python and SQL (writing a clean, maintainable, scalable, and robust code).
• Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc...
• Excellent English communication skills.

Some of the benefits you’ll enjoy working with us:

• The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
• The opportunity to form part of an amazing, multicultural community of tech experts.
• A highly competitive compensation package.
• A flexible and remote working environment.

Come and join our #ParserCommunity.

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