Senior Data Scientist

Job summary

The role involves joining an AI team focused on leveraging data and AI to drive business value. The primary responsibility is to develop and productionize forecasting models that aid critical business decisions, particularly in revenue forecasting for a large number of merchants.

Qualifications

• Minimum of 3 years of experience in data science, machine learning, or applied statistics.
• Proven experience in building and maintaining time series forecasting models in a production environment.
• Proficiency in Python and libraries such as LightGBM, XGBoost, NumPy, and scikit-learn.
• Familiarity with MLflow for model tracking and experiment management.
• Experience with cloud-based data platforms like Databricks.
• Strong skills in PySpark, Pandas, and SQL for handling large datasets.
• Experience in feature extraction from unstructured data using LLMs.
• Ability to evaluate forecasting models using relevant metrics and business-oriented performance measures.

Responsibilities

• Develop and maintain production-grade time series forecasting models.
• Work on revenue forecasting for over 100,000 merchants.
• Create product features that enhance merchant optimization use cases.
• Collaborate with data engineers to ensure robust data foundations for models.
• Engage with business stakeholders to translate forecasting needs into actionable data science solutions.

Skills

• Strong analytical and problem-solving skills.
• Ability to perform exotic feature engineering and apply non-standard modeling approaches when necessary.
• Pragmatic approach to transforming ambiguous business problems into concrete modeling strategies.

Education

• Relevant degree in data science, statistics, computer science, or a related field.

Tools

• Python, LightGBM, XGBoost, MLflow, Databricks, PySpark, Pandas, SQL.