Responsibilities
- Lead the design, development, and deployment of advanced ML models and predictive algorithms to solve critical business problems, such as churn prediction, user segmentation, and product usage forecasting.
- Serve as a technical subject matter expert, guiding the team on best practices in statistical analysis, experimentation design, and code quality.
- Partner with PMs and Engineers to translate ambiguous business questions into rigorous data science projects with actionable outcomes.
- Drive the adoption of MLOps best practices, ensuring models are scalable, reproducible, and monitored effectively in production.
- Perform deep-dive analyses on user behavior and product performance to identify opportunities for optimization and growth.
- Mentor and coach other data scientists and analysts, fostering a culture of continuous technical learning and innovation.
- Communicate complex technical findings to non-technical stakeholders through compelling data storytelling and visualization.
Requirements
- 7+ years of experience in DS, Statistics, or a related field, with a proven track record of delivering high-impact machine learning solutions.
- Expert-level proficiency in Python for data manipulation, statistical analysis, and model development (pandas, scikit-learn, numpy, etc.).
- Advanced knowledge of SQL for complex data querying and performance optimization.
- Strong hands-on experience with a breadth of modeling techniques, including: - Supervised learning (Regression, Random Forests, Gradient Boosting like XGBoost/LightGBM) - Unsupervised learning (Clustering, Dimensionality Reduction) - Time series forecasting (ARIMA, Prophet)
- Experience with dbt for data transformation and maintaining clean, reliable data pipelines.
- Demonstrated ability to deploy models into production environments and familiarity with MLOps concepts.
- Familiarity with software engineering practices (CI/CD, version control with Git, Jira).
- Strong communication skills, with the ability to influence stakeholders and explain technical concepts to business audiences.
- Expertise in developing or integrating GenAI models or AI agents into product and analytical workflows.
Nice to Have
- Experience with cloud-based machine learning platforms, specifically AWS SageMaker.
- Background in the observability.
- Advanced degree (Master’s or PhD) in a quantitative discipline.
- Proficiency in data visualization tools (e.g., Tableau, Looker) to democratize insights.
Work Arrangement
Remote (Worldwide)
Additional Information
- Visa sponsorship is not available for this position.
