Head of Data Science

We are an early-stage, high-growth fintech startup reshaping the world of Growth Capital for B2C companies.

Our multidimensional underwriting platform uses Machine Learning and AI to analyze company behavior in real time and provide intelligent, non-dilutive capital, eliminating the need for traditional venture funding.

We are looking for a visionary Head of Data Science to be as part of the founding team and to own our predictive engine, risk modeling, and ML architecture end-to-end.

As Head of Data Science, you will be responsible for building and leading the Data Science function from the ground up.

You will define the company’s ML strategy, build cutting-edge underwriting models, and create the core decision-making engine powering the product.

This is a founding-level position, with an opportunity to shape the product, the architecture, and the team culture — and have a direct impact on the trajectory of the company.

• Lead the end-to-end Data Science vision, roadmap, and execution.
• Build and scale a world-class data science and ML organization.
• Work closely with the CTO, CEO, and founding team on product, underwriting, and risk strategy.
• Define methodologies for predictive modeling, scoring, and underwriting algorithms.

• Develop multi-dimensional underwriting models for B2C companies based on behavioral, financial, and operational signals.
• Build machine-learning models (supervised, unsupervised, time-series, anomaly detection).
• Own feature engineering, model training, validation, monitoring, and continuous improvement.
• Evaluate and select data sources, frameworks, and tools.

• Work cross-functionally with engineering to design data pipelines, real-time scoring systems, ETL processes, and model deployment.
• Define data architecture to support scalable analytics and ML workloads.
• Ensure data quality, accuracy, and compliance.

• Translate noisy raw data into actionable insights and financial decision-making.
• Build robust performance monitoring systems for underwriting accuracy.
• Play a key role in defining strategic KPIs, risk thresholds, and capital allocation logic.

• 5+ years of hands-on experience in Data Science / Machine Learning.
• Experience in leading DS/ML teams (ideally as Head/Director/Lead).
• Strong background in machine learning, statistics, modeling, and algorithmic thinking.
• Hands-on experience with ML production systems (MLOps, model deployment, monitoring).
• Deep understanding of B2C data patterns (customer lifetime value, churn, funnels, revenue forecasting, etc.).
• Experience working with fintech, underwriting, credit risk, or predictive scoring models.
• Proven ability to build systems from scratch and make decisions in a fast-paced, ambiguous environment.
• Strong programming skills in Python and experience with data infrastructure (SQL, cloud environments, PyTorch/TensorFlow, MLFlow, etc.).

• Experience in capital financing products (growth capital, revenue-based financing, underwriting engines).
• Prior experience in early-stage startup and/or founding team.
• Familiarity with alternative data sources and behavioral modeling.
• Knowledge of financial metrics, revenue dynamics, and risk scoring methodologies.