דרושים » ניהול ביניים » Senior Data Scientist

We are seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.
What You'll Do:Empty heading
Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases.