Head of Data Science

At Scrambly, we are revolutionizing the rewarded advertising space currently serving over 3 million users in the USA. Over the past few years, we've grown rapidly, and we’re looking for incredible people to help us continue pushing boundaries and delivering top-tier digital solutions.

As our Head of Data Science, you will build and scale Scrambly’s data science function from the ground up. You’ll define the long-term strategy and lead hands-on execution across machine learning, personalization, experimentation, forecasting, fraud prevention, and internal decision intelligence.

This is a high-impact leadership role for someone who thrives at the intersection of product, engineering, and analytics. You will develop models that directly influence user engagement, monetization, and risk management across global consumer products.
You will initially manage an external data science/ML agency while building Scrambly’s internal data science and AI team. You will also own Scrambly’s applied AI strategy, including LLM-powered features and internal AI tools.

Key Responsibilities

• Strategy & Leadership
  • Define and own Scrambly’s data science roadmap.
  • Build and lead the data science team: hiring, mentoring, establishing standards.
  • Manage and coordinate an external ML agency until the internal team is established.
  • Collaborate closely with engineering, product, design, marketing, operations, fraud, and leadership teams to drive data-informed decisions.
  • Translate complex technical concepts into clear recommendations for business stakeholders.
  • Lead Scrambly’s applied AI/LLM strategy across product and internal tooling.
• Machine Learning & Personalization
  • Build and maintain models for personalization, recommendations, engagement prediction, churn, and LTV forecasting.
  • Deploy and evaluate ML models across online/offline pipelines with continuous retraining and monitoring.
  • Partner with engineering to integrate ML models into Scrambly’s backend and mobile/web products with performance and scalability in mind.
  • Design and integrate LLM-based capabilities such as semantic search, natural language assistance, automated content generation, or model-augmented decision engines.
  • Evaluate, fine-tune, or distill foundation models (OpenAI, Claude, Llama, Gemini, etc.) for Scrambly’s product and internal workflows.
• Fraud Detection & Risk Prevention
  • Develop advanced fraud detection systems using anomaly detection and behavioral modeling.
  • Build scoring systems for event manipulation, multi-accounting, and suspicious behavior.
  • Work with product and operations to design block rules, thresholds, TTC validation systems, and automated risk classification.
  • Monitor fraud trends and proactively identify emerging risks.
• Data Infrastructure & Model Ops
  • Define requirements and collaborate with engineering to build scalable data pipelines for training, inference, experimentation, and monitoring.
  • Define and implement robust MLOps practices (CI/CD for ML models, automated retraining, monitoring, versioning).
  • Ensure reliable data quality, documentation, and metadata standards across the organization.
  • Build infra for LLM workloads: vector DBs, embedding pipelines, prompt evaluation, safety checks.
• Compliance, Privacy & Responsible AI
  • Ensure data science initiatives comply with global privacy regulations (GDPR, Japan APPI, Korea PIPA, CCPA).
  • Work with the DPO/legal team to design privacy-by-design data science solutions.
  • Establish guardrails for responsible, safe, and transparent AI/LLM usage.

• 6+ years of experience in data science or ML engineering roles, at least 2+ years in a leadership or senior ownership position.
• Strong proficiency in Python, ML frameworks (TensorFlow, PyTorch, XGBoost, etc.), and analytics tooling.
• Deep experience building and deploying ML models in production environments.
• Hands-on expertise in recommendation systems, personalization, time-series forecasting and/or fraud detection models.
• Experience with data pipeline tools (Airflow, dbt, BigQuery, Snowflake, etc.) and MLOps best practices.
• Proven skills in translating business goals into data science solutions that drive measurable impact.
• Strong analytical thinking and ability to design rigorous experiments.
• Cross-functional experience with product, engineering, monetization and marketing, along with managing external vendors or agencies.
• Excellent communication skills with the ability to balance clarity, speed and business context while driving product-oriented decisions across teams.
• Experience working in fast-paced consumer/mobile product environments preferred.
• English: B2+; fluent and confident communicator, able to collaborate with multidisciplinary teams across countries.

• An opportunity to define, build and own Scrambly’s data science & AI function - with the mandate to shape vision, ship solutions, and drive measurable product impact in a fast-scaling business.
• Direct collaboration with the founders, engineering leadership, and product teams.
• Massive influence - your models and systems will shape the experiences of millions of users worldwide.
• Full-time & fully remote position
• 15 days of paid vacation days
• 5 days of paid days off
• 5 days of paid sick leave
• Maternity/Paternity leave
• National holidays by the country of your stay