Who you are

• 9+ years of experience in data science, machine learning, or advanced analytics roles, ideally in a SaaS, AdTech, or MarTech environment
• Knowledge of and experience in implementing marketing data science models such as predictive models (churn, retention, LTV), advanced segmentation and behavioral clustering
• Skilled in causal inference techniques (e.g., synthetic controls, DiD, uplift modeling, geo-experiments, CUPED) and experimentation frameworks
• Knowledge of ad ecosystems (RTB, attribution, identity graphs, bidding strategies, pixel events, campaign optimization, incrementality)
• Strong fluency in SQL and Python, with hands-on experience building and shipping production-grade ML models
• Proven track record partnering with Product to define metrics, run experiments, and shape product strategy
• Excellent data storytelling abilities — able to translate complex patterns into clear, action-oriented recommendations for cross-functional partners
• Comfortable navigating ambiguous problem spaces and driving long-term analytical strategy

What the job involves

• Lead the design, development, and deployment of ML models that predict and influence customer behavior — including churn, retention, activation, lifetime value, and lifecycle transitions
• Build behavioral segmentation frameworks, uplift models, and propensity scoring used across product, lifecycle marketing, and account strategy
• Drive insights for core product areas (audience targeting, measurement, bidding, onboarding, campaign performance) using a mix of causal inference, predictive modeling, and experimentation

Benefits

• Healthcare
• Paid Time Off
• Up To 12 Weeks Paid Parental Leave
• Wellness Programs
• Comprehensive Learning & Development Program
• Home Office Setup Support as Needed