Data Scientist/ Sr. Data Scientist

• Curious and creative mindset: You thrive in solving complex, undefined problems and have a passion for exploring new ideas. You’re not afraid to ask the tough questions or present innovative approaches, and you can distill your insights for non-technical audiences.
• Strong technical expertise: You have hands-on experience building data science solutions from concept to production, leveraging open-source tools and modern cloud computing platforms. You can work comfortably with massive datasets.
• Statistical prowess: You’ve built, validated, and fine-tuned models. You know your way around a confusion matrix, ROC curves, clustering, classification, time series analysis, and deep learning techniques.
• Customer and product focus: You're driven by a passion for fintech and enhancing the banking experience. You ensure that your work directly contributes to business outcomes.

• Translate complex business problems into analytical questions.
• Design and implement data-driven solutions for a variety of use cases.
• Develop and implement advanced machine learning models, such as credit scoring, fraud detection, behavioral analytics, and optimization models.
• Create analytics dashboards for actionable insights and reporting, improving decision-making processes.
• Manage end-to-end data science projects, including planning, execution, and post-implementation monitoring.
• Continuously improve data science practices, tools, and frameworks to ensure scalability and efficiency.
• Collaborate closely with product and engineering teams to integrate data models into core products.
• Present and explain findings to both technical and non-technical stakeholders, ensuring clarity and impact.
• Mentor junior data scientists and offer technical guidance to support team growth and success.

• Degree in a quantitative discipline: Mathematics, Statistics, Data Science, Computer Science, Statistics, Engineering, or a related field.
• 5+ years of experience in data analytics, data management, or related roles.
• Solid understanding of statistical models, including their assumptions and limitations.
• Experience developing credit models in the Retail/SME space (e.g., credit cards, merchant analytics, fraud detection).
• Strong proficiency in Python, R, or SQL; experience in multiple languages is a plus.
• Hands-on experience in the model development lifecycle (training, validation, tuning, monitoring).
• Familiarity with data visualization tools such as Tableau and/or Metabase; dashboard creation experience is an advantage.
• Strong understanding of financial industry best practices.
• Experience with cloud platforms (AWS, Azure, Google Cloud) for data processing and model deployment is a plus.
• Strong understanding of data management principles and infrastructure is a plus.

• Challenging role in a startup environment with strong growth ambitions.
• Opportunities for professional growth and development.
• A dynamic and innovative work environment.
• Competitive compensation and benefits

Nikel