Data Scientist

Job Description

About the Role:

We’re looking for a Data Scientist who thrives on building predictive models that directly shape business decisions — not dashboards that collect dust. You’ll join a fast-paced Decision Science team working alongside product managers, data engineers, and revenue strategists to design, deploy, and iterate on models that influence how we allocate marketing spend, optimize user flows, and anticipate churn.

Key Responsibilities:

• Develop and productionize predictive models (e.g., LTV forecasting, propensity scoring, dynamic pricing) using real-time and batch data sources.
• Collaborate with product teams to translate model outputs into action, including experimentation design, rollout logic, and KPI tracking.
• Own end-to-end model lifecycle — from initial EDA and feature engineering to A/B test design, deployment, and post-deployment monitoring.
• Investigate counterintuitive trends or spikes in key metrics using structured diagnostics and root-cause analysis frameworks.
• Build reusable, well-documented pipelines using tools like dbt, Airflow, and feature stores.
• Partner with data engineering to refactor flaky pipelines or resolve schema mismatches that affect model stability.

Requirements:

• 3–5 years of experience in a data science role where you’ve deployed models into a production environment and owned business outcomes.
• Fluent in Python, with demonstrated use of scikit-learn, XGBoost, and statsmodels; bonus for experience with MLflow, TensorFlow Extended, or Bayesian optimization libraries.
• Proficient in SQL, with an understanding of query tuning, window functions, and CTEs for large-scale data manipulation.
• Comfortable debugging issues in Airflow DAGs, writing unit tests for data pipelines, and collaborating with data engineers on schema design.
• Proven ability to communicate model assumptions, limitations, and impact to non-technical stakeholders (e.g., revenue, growth, ops).
• Experience designing experiments or uplift models, including understanding of statistical power, sample size, and model drift.
• Familiarity with CI/CD for data science (e.g., GitHub Actions, testing datasets, model version control).

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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