Top Hybrid Data Science Jobs

Lead development, maintenance, and monitoring of credit risk models for lending portfolios. Use SQL and Python to build pipelines, perform EDA, forecast losses, automate dashboards, produce audit-ready documentation, support model governance/validation, and communicate insights to stakeholders.

Lead and build a US-based data science capability while remaining hands-on: write code, design, deploy, and maintain production ML models, mentor junior data scientists and ML engineers, establish MLOps and data-science workflows on GCP, and align initiatives with product and global teams to deliver measurable business value.

The Lead Data Scientist will manage projects on credit risk and business intelligence analytics, leveraging statistical models to provide insights for financial services clients. Responsibilities include developing solutions, leading client engagements, and mentoring junior staff.

Lead finance-focused consulting engagements to design performance management frameworks, KPIs, budgeting, forecasting, and financial modeling. Analyze financial data, build visualization and data-driven insights, manage teams, mentor staff, and drive process optimization and cost‑reduction initiatives to improve client financial performance and decision-making.

The Data Scientist will build predictive models, design data pipelines, conduct analyses, and deploy solutions in a collaborative environment.

Technical lead for Growth Analytics: partner with Growth/Marketing/Sales to identify opportunities, design experiments and statistical models, build scalable measurement frameworks, mentor junior data scientists, translate business questions into analytic solutions, and communicate insights to drive acquisition, activation, retention, and reactivation.

Lead causal inference (A/B testing), machine learning, and analytics projects; analyze behavioral and transaction data to drive actionable insights; automate reports, diagnose data issues, and support market analyses; communicate findings to technical and non-technical stakeholders; mentor team members and drive strategic analytics initiatives.

The Advanced Data Science Manager leads a team of data scientists, develops data science strategies, manages client projects, and drives business development while providing thought leadership and mentoring.

As a Senior Data Scientist, you will develop machine learning models, automate data pipelines, and implement AI solutions while collaborating with engineers and stakeholders to meet customer needs.

The role involves analyzing complex data related to private markets, developing data models, creating visualizations, and collaborating on data-driven products.