Lead Data Scientist

At Klivvr, data is a top priority for driving success across various functions. As a Data Science Lead, you will play a crucial role in transforming diverse financial datasets into actionable insights that drive business decisions. Your responsibilities will include designing and developing data solutions, leveraging machine learning tools, and collaborating with cross-functional teams to achieve strategic goals.

What you will do!

• Develop a deep understanding of Klivvr’s financial data landscape and associated data sources to gain insights into performance and identify optimization opportunities.
• Identify, design, and develop data solutions that support strategic initiatives and operational improvements.
• Apply machine learning tools to select features, create and optimize classifiers, and develop predictive systems.
• Enhance data collection procedures to ensure comprehensive data for developing analytic systems.
• Utilize first- and third-party data sources to deepen understanding of drivers of growth, efficiency, and customer loyalty.
• Acquire, cleanse, validate, and integrate data from various sources for discovery and model development.
• Analyze large volumes of information to identify patterns and derive actionable solutions.
• Present results clearly and propose solutions and strategies to address business challenges.
• Develop and implement an A/B testing framework to evaluate model quality and effectiveness.
• Enable a self-serve data environment using data modeling and visualization tools such as Looker, while supporting ad-hoc analysis requests as needed.
• Oversee the development and maintenance of financial alerting systems to keep relevant teams informed of incidents requiring immediate attention.
• Monitor key performance indicators to track and report on financial performance, providing data-driven insights and recommendations for optimization.

About You

• A minimum of 5 years experience in a data science role, ideally within a fintech or financial services organization.
• A background in Computer Science, Analytics Engineering, Mathematics, Statistics, Economics, or another quantitative field.
• Proficiency with Python or similar programming languages and associated data science packages.
• Proficiency in SQL (We use Google BigQuery).
• Experience with dashboard visualization tools such as Looker, Google Data Studio, Tableau, or similar.
• A strong collaborator with excellent communication skills, effective in working with cross-functional teams and managing stakeholder expectations.
• Experience in measuring the impact of data initiatives and presenting findings with clear, actionable recommendations.
• Intellectually curious, creative, and diligent, with a passion for both the business and the data.