Drive impactful analytics and machine learning initiatives across complex business operations for a partner company in the United States
Requirements
- Proven experience applying data science, machine learning, and AI end-to-end to solve business problems.
- Strong proficiency in Python and SQL for data wrangling, feature engineering, modeling, and visualization.
- Experience with model selection, evaluation, and validation; ability to diagnose overfitting/underfitting and communicate limitations.
- Expertise in experimentation and causal inference methods applied to product growth, revenue, or retention outcomes.
- Experience deploying AI tools to enhance customer insights and data workflows is a plus.
- Strong proficiency in data wrangling, feature engineering, modeling, and visualization
- Experience with model training, and validation
Responsibilities
- Analyze large, diverse datasets to extract actionable insights that inform product strategy, conversion optimization, and customer retention.
- Develop, deploy, and maintain predictive ML pipelines, including data wrangling, feature engineering, model training, and validation.
- Collaborate cross-functionally with product, engineering, sales, and analytics teams to operationalize AI-driven solutions.
- Design and evaluate experiments (A/B tests, holdouts, quasi-experiments) to validate hypotheses and quantify impact on key outcomes.
- Build and assess causal models for revenue and customer lifetime value, using appropriate metrics and validation techniques.
- Communicate findings, trade-offs, and limitations clearly to technical and non-technical stakeholders, supporting data-informed decision-making.
- Mentor junior team members and promote best practices in model development, evaluation, and analytics storytelling.
Other
- Collaborative mindset and ability to work effectively in cross-functional teams.
- Excellent communication skills with the ability to tailor insights for diverse audiences.
- Bachelor's degree or higher in a quantitative field (no specific degree mentioned)
- Ability to work in a fast-paced environment
- Enjoy solving challenging problems
