Data Scientist

About the Role

We are looking for a proactive, curious, and business-oriented Data Scientist to join our Alternative Credit Scoring team. As one of the first Data Science members in the company, you will play a key role in improving our existing scoring products, exploring new data opportunities, and developing innovative analytics solutions for the financial industry.

Beyond building models, you will act as a Data Science advocate by promoting data-driven thinking, educating stakeholders, and helping cross-functional teams understand how Data Science can solve business problems. This role is ideal for someone who enjoys building from scratch, learning independently, and taking ownership in a fast-growing environment.

Responsibilities

• Analyze large-scale datasets to generate insights and develop predictive models.

• Enhance and continuously improve existing alternative credit scoring models through feature engineering, experimentation, and model evaluation.

• Research and propose new data products, AI/ML solutions, and analytical approaches.

• Translate business problems into data-driven solutions and proactively identify opportunities to create new data products.

• Collaborate closely with Product, Engineering, and Commercial teams to deliver scalable data solutions.

• Validate and monitor model performance, and communicate analytical findings to both technical and non-technical stakeholders.

• Act as a Data Science advocate by promoting data-driven decision making, educating stakeholders, and increasing Data Science awareness across the organization.

• Develop and maintain documentation for models, features, and analytical processes.

• Stay up to date with the latest trends and best practices in Data Science, AI, and Machine Learning.

Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field.

• 2+ years of experience in Data Science, Machine Learning, Risk Analytics, or related fields.

• Strong understanding of statistics, predictive modeling, machine learning, and feature engineering.

• Proficient in Python, SQL, Jupyter Notebook, and Git/GitHub.

• Experience with Pandas, NumPy, Scikit-learn, XGBoost, LightGBM, or similar machine learning libraries.

• Familiar with cloud data platforms such as Google BigQuery, AWS, or equivalent.

• Experience evaluating classification models using metrics such as AUC, KS, Gini, Precision/Recall, PSI, and model stability is a plus.

• Experience working with alternative data, fintech, banking, financial services, or credit scoring is highly preferred.

• Experience translating business problems into analytical solutions and proactively identifying opportunities to create new data products.

• Strong communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.

• Passionate about promoting data literacy and advocating the adoption of Data Science and AI across the organization.

• Self-driven, proactive, highly curious, and able to learn independently with minimal supervision.

• Strong ownership mindset and comfortable working in a fast-paced startup environment.